API Endpoint for journals.

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            "pk": 24246,
            "title": "Both intrinsic and allophonic vowel duration matter in textsetting",
            "subtitle": null,
            "abstract": "In studies of song corpora, longer vowels have been shown to be preferentially aligned with longer notes in textsetting. Here we test this alignment preference in English in an experimental setting and replicate the finding for duration in a task where participants constructed a textsetting by placing target words in appropriate slots. We test two types of vowel duration: intrinsic duration and vowel duration that is contextually determined by the voicing of the following consonant. We show that both of these types of duration have an effect on textsetting preferences.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Music; Phonology"
                }
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            "remote_url": "https://escholarship.org/uc/item/7cb1d3jb",
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                {
                    "first_name": "Nicole",
                    "middle_name": "",
                    "last_name": "Gilroy",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                },
                {
                    "first_name": "Lev",
                    "middle_name": "",
                    "last_name": "Blumenfeld",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                },
                {
                    "first_name": "Ida",
                    "middle_name": "",
                    "last_name": "Toivonen",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                }
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            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24246/galley/20962/download/"
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            "pk": 21691,
            "title": "Boundedness is Represented in Visual and Auditory Event Cognition",
            "subtitle": null,
            "abstract": "Viewers are sensitive to the distinction between visual events with an internal structure leading to a well-defined endpoint (bounded events) and events lacking this structure and a well-defined endpoint (unbounded events). Here, we asked whether boundedness could be represented in the auditory modality in a way similar to the visual modality. To investigate this question, we trained participants with visual and auditory events on bounded or unbounded event categories in a category identification task. Later, we tested whether they could abstract the internal temporal structure of events and extend the (un)boundedness category to new examples in the same modality. These findings suggest that the principles and constraints that apply to the basic units of human experience in the visual modality have their counterparts in the auditory modality.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Audition; Event cognition; Perception"
                }
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            "remote_url": "https://escholarship.org/uc/item/15x9f213",
            "frozenauthors": [
                {
                    "first_name": "Bahar",
                    "middle_name": "",
                    "last_name": "Tarakçı",
                    "name_suffix": "",
                    "institution": "Özyeğin University",
                    "department": ""
                },
                {
                    "first_name": "Ceren",
                    "middle_name": "",
                    "last_name": "Barış",
                    "name_suffix": "",
                    "institution": "Özyeğin University",
                    "department": ""
                },
                {
                    "first_name": "Ercenur",
                    "middle_name": "",
                    "last_name": "Ünal",
                    "name_suffix": "",
                    "institution": "Özyeğin University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21691/galley/22084/download/"
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            "pk": 24071,
            "title": "Brain Breaks: Teacher Usage And Child Preference",
            "subtitle": null,
            "abstract": "Brain breaks are often used during lessons to replenish childrens' attention, but children may respond differently to the variety of brain breaks they are offered. Therefore, two studies were conducted to identify both teachers' current use of brain breaks (Study 1) as well as the types of brain breaks children prefer (Study 2). Study 1 consisted of a survey of K-2 teachers (N = 796) across the United States regarding the implementation and types of brain breaks commonly used in their classrooms. The three most common break types reported by teachers were physical activity breaks, videos, and dancing. Study 2 consisted of a forced choice task in which elementary- and middle-school students were asked to pick between two instantiations of six different break types: cognitive engagement breaks, mindfulness exercises, physical activity breaks, nature videos, coloring, and mind wandering. For each break type, children were asked to pick the instantiation they preferred as well as the one they believed would help them focus. Children were then asked to rank the six breaks they selected from most to least preferred and most to least beneficial for focusing. Data collection is ongoing \n(N = 53). Preliminary results revealed children were more likely to rank cognitive engagement breaks as their most preferred break type. Analyses within break type revealed that students preferred mazes over pattern blocks as a cognitive engagement break, color jump over calisthenics for physical activity breaks, videos of forest scenery over cows grazing for a nature video break, mandala coloring over abstract coloring as a coloring break, and viewing a poster of a starry sky over an abstract poster as a mind wandering break.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Decision making; Survey"
                }
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            "remote_url": "https://escholarship.org/uc/item/0zc1349p",
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                {
                    "first_name": "Praveen",
                    "middle_name": "",
                    "last_name": "Kumaravelan",
                    "name_suffix": "",
                    "institution": "University of Maryland, Baltimore County",
                    "department": ""
                },
                {
                    "first_name": "Audrey",
                    "middle_name": "",
                    "last_name": "Leroux",
                    "name_suffix": "",
                    "institution": "Georgia State University",
                    "department": ""
                },
                {
                    "first_name": "Karrie",
                    "middle_name": "E.",
                    "last_name": "Godwin",
                    "name_suffix": "",
                    "institution": "University of Maryland Baltimore County",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24071/galley/20963/download/"
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            "pk": 21583,
            "title": "Breadth of the Stars: Exploring Adjectival Breadth in Online Reviews",
            "subtitle": null,
            "abstract": "Language is fundamental in human cognition and communication, helping us to encode the world around us. Adjectives represent a linguistic form used extensively, particularly in the social domain. Adjectives vary in both their valence and their breadth (e.g., “punctual” is narrower than “dependable”). Variations in adjectival breadth have not been studied extensively but may have significant consequences across various domains. The present study explores how subtle distinctions in adjective use may relate to descriptions of experiences that people share. To assess linguistic breadth in online communication, we examine whether online reviews with different star ratings are associated with differences in adjectival breadth. Through an analysis of over 200,000 reviews from Amazon digital music (Study 1) and Yelp restaurants (Study 2), we find evidence that linguistic desirability and breadth of adjectives in reviews positively correlate with their ratings. Specifically, higher-rated reviews tend to use broader and more desirable adjectives. However, this relationship varies between product categories, with high-rated music reviews showing increased linguistic breadth and desirability, while top-rated restaurant reviews demonstrate a decrease in breadth. This paper contributes to understanding linguistic breadth in social media contexts, highlighting how subtle language variations in evaluations can reflect different cognitive and communicative processes.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language and thought; Language understanding; Social cognition; Big data"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6cp1k0sq",
            "frozenauthors": [
                {
                    "first_name": "Lin",
                    "middle_name": "",
                    "last_name": "Lin",
                    "name_suffix": "",
                    "institution": "University of California, Los Angeles",
                    "department": ""
                },
                {
                    "first_name": "Rick",
                    "middle_name": "",
                    "last_name": "Dale",
                    "name_suffix": "",
                    "institution": "University of California, Los Angeles (UCLA)",
                    "department": ""
                },
                {
                    "first_name": "Steve",
                    "middle_name": "",
                    "last_name": "Stroessner",
                    "name_suffix": "",
                    "institution": "University of California, Los Angeles (UCLA)",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21583/galley/21976/download/"
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        {
            "pk": 24210,
            "title": "Breaking Focus: The impact of disruptive distractions on academic task performance",
            "subtitle": null,
            "abstract": "Over time, there has been a change in how students acquire and exchange information, with laptops and smartphones becoming increasingly important. The use of technology has evolved from being restrained du to the classroom to being crucial due to the COVID-19 pandemic. As education shifts towards hybrid models, students are now expected to learn at home, which can be challenging as excessive technology usage and a lack of self-discipline can lead to more distractions. This paper examines the effects of the influence of these distractions with the help of two concepts similar to assignments in students' lives: text comprehension & memorization, as well as example-based learning, in which the function of an apparatus was to be tested and described. The results show that distraction does not affect text comprehension but decreases information retention. Additionally, participants required more trials and repetitions to understand schemes in example-based learning when distracted.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Psychology; Instruction and teaching; Learning; Reasoning; Logic"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2587r33t",
            "frozenauthors": [
                {
                    "first_name": "Jenny",
                    "middle_name": "",
                    "last_name": "Rettstatt",
                    "name_suffix": "",
                    "institution": "Chemnitz University of Technology",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "",
                    "last_name": "Brand",
                    "name_suffix": "",
                    "institution": "Chemnitz University of Technology",
                    "department": ""
                },
                {
                    "first_name": "Marco",
                    "middle_name": "",
                    "last_name": "Ragni",
                    "name_suffix": "",
                    "institution": "TU Chemnitz",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24210/galley/13806/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24210/galley/20964/download/"
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            "pk": 24184,
            "title": "Bridging (and Elaborating on) the Achievement Gap",
            "subtitle": null,
            "abstract": "Researchers have long been interested in understanding and closing the “reading gap” that exists between White and racially marginalized students. This study explored whether group differences in inference strategies (i.e., bridging and elaboration) and comprehension performance existed among college readers. Three hundred college participants who self-identified as White, Black, or Hispanic completed a think-aloud task along with measures of reading proficiency and comprehension. Results from hierarchical regression models indicated that group differences in elaborative strategies were present, but differences in bridging strategies and comprehension performance disappeared when foundational skills in reading were included in the models. The results are explained in terms of inequities in educational experiences prior to entering college.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Psychology; Discourse; Reading; Verbal protocol studies"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8kp2w01x",
            "frozenauthors": [
                {
                    "first_name": "Daniel",
                    "middle_name": "P.",
                    "last_name": "Feller",
                    "name_suffix": "",
                    "institution": "University of Memphis",
                    "department": ""
                },
                {
                    "first_name": "Ann",
                    "middle_name": "Cale",
                    "last_name": "Kruger",
                    "name_suffix": "",
                    "institution": "Georgia State University",
                    "department": ""
                },
                {
                    "first_name": "Joe",
                    "middle_name": "P",
                    "last_name": "Magliano",
                    "name_suffix": "",
                    "institution": "Georgia State University.",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24184/galley/20965/download/"
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        },
        {
            "pk": 21572,
            "title": "Bridging the Gap: Advancing Commonsense Question Answering with Integrated Multi-Modal Knowledge",
            "subtitle": null,
            "abstract": "Most current research on commonsense question answering (CQA) has focused on proposing different techniques in natural language processing and text information retrieval. However, for human cognition, retrieving and organizing desired answers from text knowledge related to commonsense questions is far less intuitive and comprehensive than it is when using multi-modal knowledge, such as related images and videos. Motivated by this, we propose a framework for trying the acquisition of diverse modal information, and embedding and integrating it into CQA tasks, further improving the performance and user experience. Specifically, this paper proposes the integration of multi-modal knowledge, including images, image description statements, image scene graphs, and knowledge sub-graphs, into a CQA system. It introduces a parallel embedding technique for this multi-modal knowledge and employs an alignment-interaction-fusion mechanism to facilitate the seamless integration of this multi-modal knowledge. Through extensive experiments, the effectiveness and superiority of our proposed method are demonstrated.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Computer Science; Reasoning; Social media analysis"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9nq7d0xf",
            "frozenauthors": [
                {
                    "first_name": "Yongqiang",
                    "middle_name": "",
                    "last_name": "Zhao",
                    "name_suffix": "",
                    "institution": "Peking University",
                    "department": ""
                },
                {
                    "first_name": "Zhi",
                    "middle_name": "",
                    "last_name": "Jin",
                    "name_suffix": "",
                    "institution": "Peking University",
                    "department": ""
                },
                {
                    "first_name": "Feng",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Academy of Military Sciences",
                    "department": ""
                },
                {
                    "first_name": "Xinhai",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "Academy of Military Sciences",
                    "department": ""
                },
                {
                    "first_name": "Donghong",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "Academy of Military Sciences",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21572/galley/11171/download/"
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21572/galley/21965/download/"
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        {
            "pk": 24039,
            "title": "Bridging the Measurement Gap: a Large Language Model Method of Assessing Open-Ended Question Complexity",
            "subtitle": null,
            "abstract": "Question-asking, an essential yet understudied activity, holds significant implications for fields such as learning, creativity, and cognitive development. The quality, and complexity in particular, of the questions are recognized as crucial factors affecting these fields. Previous research explored question complexity through Bloom's taxonomy, but measurement remains challenging. Recent advancements have enabled automated scoring of psychological tasks but have not been applied to open-ended question complexity. Here, we address this gap by employing large language model (LLM) techniques to predict human ratings of open-ended question complexity. Our results reveal that our LLM-generated complexity scores correlated strongly with human complexity ratings in both the holdout-responses (r = .73) and holdout-item set (r = .77), whilst also exceeding baseline methods tested. The research emphasizes the significance of LLMs in psychological research and their potential in automating question complexity assessment. This study also highlights exciting possibilities for usage of LLMs in education and psychology.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Education; Creativity; Language and thought; Natural Language Processing"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5k68s597",
            "frozenauthors": [
                {
                    "first_name": "Tuval",
                    "middle_name": "",
                    "last_name": "Raz",
                    "name_suffix": "",
                    "institution": "Technion - Israel Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Simone",
                    "middle_name": "",
                    "last_name": "Luchini",
                    "name_suffix": "",
                    "institution": "Pennsylvania State University",
                    "department": ""
                },
                {
                    "first_name": "Roger",
                    "middle_name": "",
                    "last_name": "Beaty",
                    "name_suffix": "",
                    "institution": "Pennsylvania State University",
                    "department": ""
                },
                {
                    "first_name": "Yoed",
                    "middle_name": "",
                    "last_name": "Kenett",
                    "name_suffix": "",
                    "institution": "Technion - Israel Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24039/galley/20966/download/"
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        },
        {
            "pk": 24044,
            "title": "Bridging Word and World: Vocal Iconicity in Chinese Child-Directed Speech and Child Production",
            "subtitle": null,
            "abstract": "This study examines three types of vocal iconicity—sound effects, onomatopoeia, and iconic prosody—in Chinese child-directed speech (CDS), adult-directed speech (ADS), and child production. We analyzed a corpus of semi-spontaneous ADS and CDS from forty Chinese mother-child dyads, where the children were 18 and 24 months old. Our findings revealed that (1) mothers used significantly more sound effects and iconic prosody, but not onomatopoeias, in CDS compared to ADS. Interestingly, mothers' iconic prosody was also acoustically more congruent with lexical meanings; (2) The frequency of sound effects was lower than iconic prosody but higher than onomatopoeias; and (3) Chinese children aged 18 or 24 months seldom produced onomatopoeia or iconic prosody. These findings suggest that iconicity is more prevalent and prosodically marked in CDS than in ADS, which may help children's word-to-world mapping. Also, iconic prosody is an advanced prosodic skill that is not typically developed by two-year-old children.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Development; Embodied Cognition; Language development"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3mz2j3z0",
            "frozenauthors": [
                {
                    "first_name": "Mengru",
                    "middle_name": "",
                    "last_name": "Han",
                    "name_suffix": "",
                    "institution": "East China Normal University",
                    "department": ""
                },
                {
                    "first_name": "Yiqi",
                    "middle_name": "",
                    "last_name": "Nie",
                    "name_suffix": "",
                    "institution": "East China Normal University",
                    "department": ""
                },
                {
                    "first_name": "Yan",
                    "middle_name": "",
                    "last_name": "Gu",
                    "name_suffix": "",
                    "institution": "University of Essex",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24044/galley/20967/download/"
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        },
        {
            "pk": 21381,
            "title": "Brown Bear, Brown Bear, what do you see? Speaker use more redundant color adjectives when speaking to children than adults",
            "subtitle": null,
            "abstract": "Speakers are often over-informative, referring to the color and shape of a referent even when all objects in a scene are unique. Interestingly, this helps listeners locate the target. If speakers are indeed sensitive to listeners' online processing demands, they should be more over-informative when addressing someone whose processing is especially slow. Here we show that English-speaking adults produce more redundant color adjectives when speaking to children than adults (Exp 1); that although Spanish-speakers produce fewer redundant color adjectives than English-speakers overall, they too do so more often for children (Exp 2); that these results are independent of experience with young children (Exp 3), and that children themselves (ages 4-10) are more over-informative when speaking to younger children than adults (Exps 4 and 5). Collectively, these results suggest that sensitivity to listeners' online processing demands is robust, emerges early in development, and may be especially tailored to young learners.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Development; Language Production; Pragmatics; Cross-linguistic analysis"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8x06j9f6",
            "frozenauthors": [
                {
                    "first_name": "Maya",
                    "middle_name": "",
                    "last_name": "Taliaferro",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Laura",
                    "middle_name": "",
                    "last_name": "Schulz",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21381/galley/10980/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21381/galley/21826/download/"
                }
            ]
        },
        {
            "pk": 24265,
            "title": "Building Abstraction: The Role of Representation and Structural Alignment in Learning Causal System Categories",
            "subtitle": null,
            "abstract": "The present study examined the role of detecting the initial causal system model followed by engaging in active vs. passive structural alignment in recognizing the key causal principles in subsequent novel examples. The results echo prior research on the benefit of analogical comparison in learning relational categories: participants who were prompted to compare outperformed participants in the baseline condition. Moreover, while the accurate representation of the causal system predicted noticing the relational structure in novel examples, making more accurate relational mappings made participants more likely to notice the structure above and beyond having an accurate representation. These findings offer insight into the role of active vs. passive analogical comparison and have implications for conditions that might support learning of relational categories.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Psychology; Learning; Reasoning; Representation"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6ks4716f",
            "frozenauthors": [
                {
                    "first_name": "Margarita",
                    "middle_name": "V.",
                    "last_name": "Pavlova",
                    "name_suffix": "",
                    "institution": "New Bulgarian University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24265/galley/13861/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24265/galley/20968/download/"
                }
            ]
        },
        {
            "pk": 24813,
            "title": "Building and Validating Multiword Expression Lexicons with a Case Study on Language and Conspiracy Theories",
            "subtitle": null,
            "abstract": "Psycholinguistic dictionaries or lexicons have been used for text analysis in a variety of domains, from analyzing terrorist manifestos to congressional speeches. Methods for developing these dictionaries generally focus on identifying lexemes – single semantic units – that map to psychological categories such as health (containing words like yoga, disease, neurosis), positive sentiment (happy, joy), or interpersonal conflict (fight, kill). The focus on single lexemes neglects multiword expressions (such as kick the bucket, by and large, birds of a feather), which constitute a significant portion of any language and offer similar insight into human psychology and cognition. This paper proposes a methodology for developing lexicons of multiword expressions of psychological significance, and addresses the considerations specific to identifying and validating multiword expressions. Using this methodology, I developed two lexicons of multiword expressions that correspond to two cognitive processes and used them to analyze qualitative text data discussing belief in conspiracy theories.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language and thought; Pragmatics; Case studies; Corpus studies"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/76m173pr",
            "frozenauthors": [
                {
                    "first_name": "Emily",
                    "middle_name": "",
                    "last_name": "Klein",
                    "name_suffix": "",
                    "institution": "University at Albany",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
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                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24813/galley/20969/download/"
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            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24813/galley/14411/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24813/galley/18268/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24813/galley/20969/download/"
                }
            ]
        },
        {
            "pk": 24719,
            "title": "Can a Causal Relational Matching-to-Sample Task Reveal Abstract Reasoning Abilities in Preschool Children?",
            "subtitle": null,
            "abstract": "The relational matching-to-sample task (RMTS) is a gold standard in measuring abstract concepts. Most preschoolers and non-human animals do not spontaneously succeed in the classic, two-item version of the task. It is debated whether this failure indicates a lack of abstract reasoning ability, perhaps linked to limited language capabilities, or rather stems from learned biases for other bases of matching. We developed a physical, causal RMTS task for 4- to 5-year-old children based on matching the weight relations within object pairs by asking them to align two balance scale apparatuses. We presented conflicting object matches in half of the trials and a transfer phase with a new set of stimuli. By age five, children benefitted from the causal context of the task, suggesting that not solely abstract reasoning abilities but other factors, like biases to match individual object features, influence their performance in classic arbitrary RMTS tasks.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Causal reasoning; Concepts and categories; Development; Reasoning"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6k59h976",
            "frozenauthors": [
                {
                    "first_name": "Elisa",
                    "middle_name": "",
                    "last_name": "Felsche",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Evolutionary Anthropology",
                    "department": ""
                },
                {
                    "first_name": "Luke",
                    "middle_name": "",
                    "last_name": "Maurits",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Evolutionary Anthropology",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "Benjamin Moritz",
                    "last_name": "Haun",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Evolutionary Anthropology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24719/galley/20970/download/"
            },
            "galleys": [
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24719/galley/14317/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24719/galley/18171/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24719/galley/20970/download/"
                }
            ]
        },
        {
            "pk": 21359,
            "title": "Can Children Learn Functional Relations Through Active Information Sampling?",
            "subtitle": null,
            "abstract": "Functional relations are prevalent in everyday life and science. Do children have intuitive knowledge of functional relations, and can they learn these relations by active information gathering (i.e., choosing a few input values and observing the corresponding outputs)? We found that 6- to 9-year-olds can learn different families of functions (linear, Gaussian, and exponential) through both informative data provided by an experimenter and data they gather from the environment for themselves. Overall, children learn linear functions more accurately than non-linear functions. When choosing data points to learn about, some children select highly similar points that only shed light on a narrow region of a function, while others choose more variable inputs and gain a more holistic view of a function. Children who use this latter, globally informative strategy have higher learning accuracy, particularly for non-linear functions. Results suggest that children are in the process of developing effective strategies for active function learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Causal reasoning; Cognitive development; Learning; Reasoning"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9nj772h9",
            "frozenauthors": [
                {
                    "first_name": "Caiqin",
                    "middle_name": "",
                    "last_name": "Zhou",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                },
                {
                    "first_name": "Rebekah",
                    "middle_name": "",
                    "last_name": "Gelpi",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Chris",
                    "middle_name": "",
                    "last_name": "Lucas",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Daphna",
                    "middle_name": "",
                    "last_name": "Buchsbaum",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21359/galley/10958/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21359/galley/21804/download/"
                }
            ]
        },
        {
            "pk": 24712,
            "title": "Can children leverage consensus and source independence to get better advice?",
            "subtitle": null,
            "abstract": "Young children, like adults, conform to group consensus. However, it is unclear when children develop more sophisticated intuitions about how the composition of groups, the way in which they acquire and aggregate information, impacts advice quality. This experiment assessed children's developing sensitivity to source independence - that is, do they understand that statistically independent sources of information are more valuable than correlated ones? Children (5-to-11-year-olds, N=106) and teenagers and adults (N=99) played a space exploration game in which they made multiple 2AFC decisions based on the advice of 8 friendly aliens. Across trials and participants, we manipulated consensus (the relative number of advisers endorsing each option) and source diversity (the relative number of independent advisers endorsing each option). \nResults indicated that children were able to detect the correlations between sources, but their ability to exploit this knowledge was late emerging, likely in the early adolescence years.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Decision making; Learning; Social cognition"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0s04g04x",
            "frozenauthors": [
                {
                    "first_name": "Oana",
                    "middle_name": "",
                    "last_name": "Stanciu",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                },
                {
                    "first_name": "Azzurra",
                    "middle_name": "",
                    "last_name": "Ruggeri",
                    "name_suffix": "",
                    "institution": "Technical University Munich",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24712/galley/20971/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24712/galley/14310/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24712/galley/18157/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24712/galley/20971/download/"
                }
            ]
        },
        {
            "pk": 24811,
            "title": "Can deep convolutional networks explain the semantic structure that humans see in photographs?",
            "subtitle": null,
            "abstract": "In visual cognitive neuroscience, there are two main theories about the function of the ventral visual system. One suggests that it serves to classify objects (H1); the other suggests that it generates intermediate representations from which people can generate verbal descriptions, actions, and other kinds of information (H2). To adjudicate these, we trained two deep convolutional AlexNet models on 330,000 images belonging to 86 classes, representing the intersection of Ecoset images and the semantic norms collected by the Leuven group. One model was trained to produce category labels (H1) , the other to generate all of an item's semantic features (H2). The two models learned very different representational geometries throughout the network. The representations acquired by the feature-generating model aligned better with human-perceived similarities amongst images, and better predicted human judgments in a triadic comparison task. The results thus support H2.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Cognitive Neuroscience; Representation; Computational Modeling; Neural Networks"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9s283743",
            "frozenauthors": [
                {
                    "first_name": "Siddharth",
                    "middle_name": "",
                    "last_name": "Suresh",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                },
                {
                    "first_name": "Wei-Chun",
                    "middle_name": "",
                    "last_name": "Huang",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                },
                {
                    "first_name": "Kushin",
                    "middle_name": "",
                    "last_name": "Mukherjee",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                },
                {
                    "first_name": "Timothy",
                    "middle_name": "T",
                    "last_name": "Rogers",
                    "name_suffix": "",
                    "institution": "University of Wisconsin- Madison",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
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                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24811/galley/20972/download/"
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24811/galley/14409/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24811/galley/18266/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24811/galley/20972/download/"
                }
            ]
        },
        {
            "pk": 24648,
            "title": "Can epistemic vigilance explain the underuse of social information? Evidence that a competitive incentive favoured dishonest advice and reduced the influence of social information.",
            "subtitle": null,
            "abstract": "Cultural evolutionary theory has shown that social learning is adaptive across a broad range of conditions. However, humans frequently under-utilise beneficial social information in experimental settings – a phenomenon termed egocentric discounting. We tested the hypothesis that influence is affected by expected reliability using a two-player online task in which both participants answered the same questions in series. After a first attempt, player 2 saw either advice from player 1 or their actual answer (spying). In addition, we manipulated the payoff structure of the task such that it had either a cooperative, competitive, or neutral incentive. As predicted, advice was least honest and social information overall had the least influence in the competitive condition. Player 2 also chose to spy rather than receive advice when offered the choice. Unexpectedly and regardless of the payoff structure, advice was more influential when player 2 could choose information but spying was more influential otherwise.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Anthropology; Psychology; Behavioral Science; Evolution; Learning; Computer-based experiment"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0185s54c",
            "frozenauthors": [
                {
                    "first_name": "Robin",
                    "middle_name": "",
                    "last_name": "Watson",
                    "name_suffix": "",
                    "institution": "Arizona State University",
                    "department": ""
                },
                {
                    "first_name": "Thomas J. H.",
                    "middle_name": "",
                    "last_name": "Morgan",
                    "name_suffix": "",
                    "institution": "Arizona State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
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                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24648/galley/20973/download/"
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24648/galley/14246/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24648/galley/18036/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24648/galley/20973/download/"
                }
            ]
        },
        {
            "pk": 21494,
            "title": "Can Generative Multimodal Models Count to Ten?",
            "subtitle": null,
            "abstract": "The creation of sophisticated AI systems that are able to process and produce images and text creates new challenges in assessing the capabilities of those systems.\nWe adapt a behavioral paradigm from developmental psychology  to characterize the counting ability of a model that generates images from text. We show that three model scales of the Parti model (350m, 3B, and 20B parameters respectively) each have some counting ability, with a significant jump in performance between the 350m and 3B model scales. We also demonstrate that it is possible to interfere with these models' counting ability simply by incorporating unusual descriptive adjectives for the objects being counted into the text prompt. We analyze our results in the context of the knower-level theory of child number learning. Our results show that we can gain experimental intuition for how to probe model behavior by drawing from a rich literature of behavioral experiments on humans, and, perhaps most importantly, by adapting human developmental benchmarking paradigms to AI models, we can characterize and understand their behavior with respect to our own.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Computer Science; Psychology"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8kz5787g",
            "frozenauthors": [
                {
                    "first_name": "Sunayana",
                    "middle_name": "",
                    "last_name": "Rane",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Alexander",
                    "middle_name": "",
                    "last_name": "Ku",
                    "name_suffix": "",
                    "institution": "Google DeepMind",
                    "department": ""
                },
                {
                    "first_name": "Jason",
                    "middle_name": "",
                    "last_name": "Baldridge",
                    "name_suffix": "",
                    "institution": "Google",
                    "department": ""
                },
                {
                    "first_name": "Ian",
                    "middle_name": "",
                    "last_name": "Tenney",
                    "name_suffix": "",
                    "institution": "Google Research",
                    "department": ""
                },
                {
                    "first_name": "Tom",
                    "middle_name": "",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Been",
                    "middle_name": "",
                    "last_name": "Kim",
                    "name_suffix": "",
                    "institution": "Google",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21494/galley/11093/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21494/galley/21939/download/"
                }
            ]
        },
        {
            "pk": 24163,
            "title": "Can Grammatical Gender Override Gender Stereotypes?",
            "subtitle": null,
            "abstract": "Empirical evidence shows that gendered languages influence speaker's perception of the gender of animate and inanimate nouns. In this framework, we aimed to explore whether gram-matical gender can override gender stereotypes. One hundred fourteen native Greek speakers whose second language was English were asked to match stereotypically male- and female-associated nouns presented in Greek or in their English trans-lation with a male or female face. The nouns denoted agency and communality. Participants were presented with nouns both congruent and incongruent in terms of conceptual and gram-matical gender. Responses for both Greek and English nouns were provided consistently with gender stereotypes. Critically, although responses were not dominated by grammatical gender, for female-associated nouns, the presence of grammatically masculine gender reduced female responses. Moreover, participants assigned a male face faster for male-associated nouns than for female associated nouns irrespective of grammatical gender.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language and thought; Social cognition; Computer-based experiment"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3hg0h37v",
            "frozenauthors": [
                {
                    "first_name": "Nikoletta",
                    "middle_name": "",
                    "last_name": "Galeraki",
                    "name_suffix": "",
                    "institution": "Deree, The American College of Greece",
                    "department": ""
                },
                {
                    "first_name": "Eleni",
                    "middle_name": "",
                    "last_name": "Orfanidou",
                    "name_suffix": "",
                    "institution": "Deree, The American College of Greece",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24163/galley/13759/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24163/galley/20974/download/"
                }
            ]
        },
        {
            "pk": 24737,
            "title": "Can People Accurately Draw Statistical Inferences from Dot Plots?",
            "subtitle": null,
            "abstract": "What sorts of graphical formats best convey effect size and degree of certainty of a finding? Confidence intervals are commonly used to show uncertainty, yet lay people and experts fail to correctly interpret their meaning. There has been a recent push to present individual data points rather than only presenting aggregated summary statistics (e.g., means, confidence intervals, lines of best fit). But it is unclear how well people can aggregate raw data presented in a graphical format. Across two studies, we presented participants with hypothetical study outcomes of two independent groups in three graph styles: dot plots, mean with 95% confidence interval (CI) plots, combined plots, and bee plots. We asked participants to make judgments about the effect size using the Common Language Effect Size or Bayes Factors. Participants were more likely to underestimate effect sizes and Bayes Factors for dot plots and bee plots compared to mean + 95% CI plots and combined plots. These findings suggest that people have trouble making statistical inferences when presented with raw data points in graphs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Reasoning; Statistical learning"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3mt8j5nk",
            "frozenauthors": [
                {
                    "first_name": "Sara",
                    "middle_name": "",
                    "last_name": "Jaramillo",
                    "name_suffix": "",
                    "institution": "University of Pittsburgh",
                    "department": ""
                },
                {
                    "first_name": "Benjamin",
                    "middle_name": "",
                    "last_name": "Rottman",
                    "name_suffix": "",
                    "institution": "University of Pittsburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24737/galley/20975/download/"
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24737/galley/14335/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24737/galley/18193/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24737/galley/20975/download/"
                }
            ]
        },
        {
            "pk": 23983,
            "title": "Can reinforcement learning model learning across development? Online lifelong learning through adaptive intrinsic motivation",
            "subtitle": null,
            "abstract": "Reinforcement learning is a powerful model of animal learning in brief, controlled experimental conditions, but does not readily explain the development of behavior over an animal's whole lifetime.  In this paper, we describe a framework to address this shortcoming by introducing the single-life reinforcement learning setting to cognitive science. We construct an agent with two learning systems: an extrinsic learner that learns within a single lifetime, and an intrinsic learner that learns across lifetimes, equipping the agent with intrinsic motivation. We show that this model outperforms heuristic benchmarks and recapitulates a transition from exploratory to habit-driven behavior, while allowing the agent to learn an interpretable value function. We formulate a precise definition of intrinsic motivation and discuss the philosophical implications of using reinforcement learning as a model of behavior in the real world.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Philosophy; Learning; Machine learning; Neural Networks"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1td977rv",
            "frozenauthors": [
                {
                    "first_name": "Kai",
                    "middle_name": "J",
                    "last_name": "Sandbrink",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Brian",
                    "middle_name": "",
                    "last_name": "Christian",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Linas",
                    "middle_name": "M.",
                    "last_name": "Nasvytis",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Christian",
                    "middle_name": "",
                    "last_name": "Schroeder de Witt",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Patrick",
                    "middle_name": "",
                    "last_name": "Butlin",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/23983/galley/13577/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/23983/galley/20976/download/"
                }
            ]
        },
        {
            "pk": 24199,
            "title": "Can we Google That?: Children's Beliefs about the Capacities of Three Technological Devices",
            "subtitle": null,
            "abstract": "This study examines 205 4- to 12-year-old children's beliefs about the abilities of three technological informants (the internet as a whole, Google search, and Amazon's Alexa smart speaker) to answer questions about celebrity and non-celebrity people and near future and far future events. The results indicate that, with increasing age, children increasingly indicate that these sources can accurately answer questions about near future events and celebrities but not about non-celebrities or far future events. Although children increasingly indicate that these sources cannot tell them about everyday people, the oldest children in the sample believe that the internet is more likely to be able to tell you about non-celebrities than Alexa or a Google search. Children's understanding of the capacities of technology change with age and information type, perhaps reflecting changes in children's experiences online. Implications for children's learning and understanding of privacy are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Development; Human-computer interaction"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/20r8g0v2",
            "frozenauthors": [
                {
                    "first_name": "Lauren",
                    "middle_name": "",
                    "last_name": "Girouard-Hallam",
                    "name_suffix": "",
                    "institution": "University of Michigan",
                    "department": ""
                },
                {
                    "first_name": "Judith",
                    "middle_name": "",
                    "last_name": "Danovitch",
                    "name_suffix": "",
                    "institution": "University of Louisville",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24199/galley/13795/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24199/galley/20977/download/"
                }
            ]
        },
        {
            "pk": 21711,
            "title": "Capable but not cooperative? Perceptions of ChatGPT as a pragmatic speaker",
            "subtitle": null,
            "abstract": "Pragmatic implicature derivation presupposes that the cooperative principle is observed and critically depends on interlocutors expecting each other to behave cooperatively. It is much less clear, however, whether people extend this assumption to communication with artificial agents. People might therefore not draw the same pragmatic inferences when interacting with an artificial agent as they would with other conversationally competent humans, even if the agent is in principle believed to be similarly competent. In our study, we ask participants to interpret messages in a pragmatic reference game which they are told were generated by ChatGPT. Additionally, participants report whether they believe ChatGPT to be capable of the reasoning needed to select the optimal message. We observe a noteworthy discrepancy: in the reference game, participants interpret ChatGPT's messages less pragmatically than those of another adult human, but in the post-test questionnaire, they overwhelmingly rate ChatGPT's pragmatic ability very highly.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Human-computer interaction; Intelligent agents; Pragmatics"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1c381535",
            "frozenauthors": [
                {
                    "first_name": "Alexandra",
                    "middle_name": "",
                    "last_name": "Mayn",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Jia",
                    "middle_name": "",
                    "last_name": "Loy",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Vera",
                    "middle_name": "",
                    "last_name": "Demberg",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21711/galley/11310/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21711/galley/22104/download/"
                }
            ]
        },
        {
            "pk": 24575,
            "title": "Capturing Asymmetric Bias in Probability Judgements",
            "subtitle": null,
            "abstract": "Individuals make biased and variable probability judgements. Recent models such as the Bayesian Sampler (Zhu, et al., 2020), Probability Theory Plus Noise (Costello & Watts, 2014), and the Quantum Sequential Sampler (Huang et al., 2023) capture a wide range of effects by assuming people are biased towards indifference (i.e., 0.5). However, in some experiments participants instead showed asymmetric bias, defined as a pull toward non-0.5 values. We investigated asymmetric bias in 5 experiments, where participants judged the probabilities of dice rolls. While participants' judgements were independent of whether they were in a high or low probability environment or the number of alternative options displayed, participants showed a bias toward low (<0.5) estimates. Furthermore, participants showed the highest variability for judgements below 0.5. This latter effect can be captured by an asymmetric prior in the Bayesian Sampler, but not by the biasing mechanisms in the other models.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Behavioral Science; Bayesian modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/01275831",
            "frozenauthors": [
                {
                    "first_name": "Aidan",
                    "middle_name": "",
                    "last_name": "Tee",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Joakim",
                    "middle_name": "",
                    "last_name": "Sundh",
                    "name_suffix": "",
                    "institution": "Uppsala University",
                    "department": ""
                },
                {
                    "first_name": "Adam",
                    "middle_name": "",
                    "last_name": "Sanborn",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Nick",
                    "middle_name": "",
                    "last_name": "Chater",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24575/galley/20978/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24575/galley/14172/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24575/galley/20978/download/"
                }
            ]
        },
        {
            "pk": 21436,
            "title": "Capturing stage-level and individual-level information from photographs: Human-AI comparison",
            "subtitle": null,
            "abstract": "This study explores human capabilities in distinguishing and recognizing entities that change over time from those that do not. We specifically investigate the linguistic distinction between \"individual-level predicates\" (ILPs) and \"stage-level predicates\" (SLPs). Our empirical approach focuses on how humans visually distinguish these two types. We performed a corpus analysis, in which a set of image captions were randomly extracted and annotated by experts with either SLP or ILP labels. The findings indicated a predominance of SLPs over ILPs in the image captions. We then performed automatic annotation on a large dataset of image captions and conducted a machine-learning experiment on image classification based on ILSs and SLPs. Our results demonstrated that SLPs were identified with high accuracy, while ILPs were identified with about chance level, substantially lower than human capabilities. Given the analyses, we discuss what features of the image contribute to distinguishing between ILPs and SLPs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Language understanding; Machine learning; Representation; Semantics; Corpus studies"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/00b1f88b",
            "frozenauthors": [
                {
                    "first_name": "Yuri",
                    "middle_name": "",
                    "last_name": "Sato",
                    "name_suffix": "",
                    "institution": "Ochanomizu University",
                    "department": ""
                },
                {
                    "first_name": "Ayaka",
                    "middle_name": "",
                    "last_name": "Suzuki",
                    "name_suffix": "",
                    "institution": "Chiba University",
                    "department": ""
                },
                {
                    "first_name": "Koji",
                    "middle_name": "",
                    "last_name": "Mineshima",
                    "name_suffix": "",
                    "institution": "Keio University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21436/galley/11035/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21436/galley/21881/download/"
                }
            ]
        },
        {
            "pk": 21321,
            "title": "Career Paths beyond the Tenure Track for Cognitive Scientists",
            "subtitle": null,
            "abstract": "Cognitive science research has far-reaching implications, but many graduate students are trained solely for tenure-track faculty positions. Academic training develops a wide range of skills in behavioral research, literature reviewing, data analysis, scientific publishing, grant writing, teaching, and student mentorship. These skills have direct application in many other careers, but training within academia typically neglects to address how these skills translate to other work environments and career paths. As growth in the number of doctoral trainees continues to outpace permanent academic positions (Kolata, 2016; Larson et al., 2013; Lederman, 2016), more doctoral recipients have been seeking employment beyond faculty positions and academia (National Science Board, 2018). Those who are interested in exploring alternative career paths may not know where to turn for guidance. Our goal in this professional development workshop is to offer such guidance and an opportunity to network with scholars in similar situations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Other; Behavioral Science; Cognitive development; UX; Statistics; Survey"
                }
            ],
            "section": "Workshops",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6fs3j3t8",
            "frozenauthors": [
                {
                    "first_name": "Carissa",
                    "middle_name": "L",
                    "last_name": "Shafto",
                    "name_suffix": "",
                    "institution": "Brightfield Strategies, LLC",
                    "department": ""
                },
                {
                    "first_name": "Vanessa",
                    "middle_name": "",
                    "last_name": "Simmering",
                    "name_suffix": "",
                    "institution": "Doctrina Consulting, LLC",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21321/galley/10920/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21321/galley/15685/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21321/galley/21766/download/"
                }
            ]
        },
        {
            "pk": 21622,
            "title": "Caregiver presence promotes judgements of exploration",
            "subtitle": null,
            "abstract": "The decision to explore a novel option or exploit a known one — referred to as the explore-exploit trade-off — has received much attention from diverse fields of research, ranging from computer science to developmental psychology. However, much of the work on this topic has focused exclusively on an individual agent acting alone, a scenario that does not fully capture the rich social dynamics of human decision-making. In particular,  the presence and participation of others can theoretically influence the decision to explore or exploit. One factor which may affect how individuals navigate the explore-exploit tradeoff is  the presence of caregivers, who can help buffer the downside costs of more exploratory decision making. Across two pre-registered studies, we investigated whether children and adults predicted more or less exploratory behavior in the presence of a caregiver. In Study 1,  we presented U.S. American children (N=87, ages 4 to 8) with vignettes of other children faced with the choice of exploring a novel option or exploiting a known one across a range of domains.  In the vignettes, the characters either faced these decisions alone or in the presence of a parent. In Study 2, we presented the same vignettes to U.S. American adults (N=79). Across both studies, and as predicted, we found that both children and adults believed others would be more exploratory in the presence of caregivers. These results add important nuance to our understanding of how individuals navigate the explore-exploit tradeoff, and highlight the role of the social context in shaping these decisions.  We aim to build on these results on future work centralizing the role and function of care in decision-making and exploration.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Decision making; Learning; Social cognition"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6s33x461",
            "frozenauthors": [
                {
                    "first_name": "Annya",
                    "middle_name": "",
                    "last_name": "Dahmani",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Dorsa",
                    "middle_name": "",
                    "last_name": "Amir",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Ashley",
                    "middle_name": "J",
                    "last_name": "Thomas",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Alison",
                    "middle_name": "",
                    "last_name": "Gopnik",
                    "name_suffix": "",
                    "institution": "University of California at Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21622/galley/11221/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21622/galley/14530/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21622/galley/22013/download/"
                }
            ]
        },
        {
            "pk": 24092,
            "title": "Cascades, Leaps, and Strawmen: How Explanations Evolve",
            "subtitle": null,
            "abstract": "Explanations are social, and when people try to explain something, they usually seek input from others. We present a simple theory of how people use the explanations they encounter as clues to the broader landscape of possible explanations, informing their decision to exploit what has been found or explore new possibilities. The challenge of coming up with novel explanations draws people to exploit or imitate appealing ones (information cascades); this draw increases as less appealing alternatives become more distant (the ``strawman'' effect). Conversely, pairs of low-quality explanations promote exploratory behavior or long-leaps away from observed attempts, and pairs of divergent high-quality explanations can lead to merging and syncretism. We use a transmission-chain experiment to test, and confirm, these predictions. Intriguingly, we also find that while people imitate good explanations, their imitations often fall short in quality. Our work provides new insight into how collective exploration can be promoted, or stalled, by implicit information about what is yet to be discovered.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Philosophy; Psychology; Causal reasoning; Learning; Reasoning"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5qr6m4nb",
            "frozenauthors": [
                {
                    "first_name": "Kara",
                    "middle_name": "",
                    "last_name": "Kedrick",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Kevin",
                    "middle_name": "J.S.",
                    "last_name": "Zollman",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Simon",
                    "middle_name": "",
                    "last_name": "DeDeo",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24092/galley/13686/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24092/galley/20979/download/"
                }
            ]
        },
        {
            "pk": 21704,
            "title": "Category Learning in Context: Modelling an Assimilation Process in Self-regulated Category Learning",
            "subtitle": null,
            "abstract": "Category learning, a fundamental cognitive ability, is significantly influenced by variability. In this research, we propose a model describing how people adjust information search in self-regulated category learning to the level of category variability. Participants in the self-regulated category learning task sampled from two categories until they felt confident in categorizing novel objects. Our model assumes an influence of the variability of the focal and counter category on sampling by considering a within-category and between-category processes. In both processes, variability is quantified using an information-theoretic measure. Within this model, we test if a between-category process can be better conceptualized as either a contrasting or an assimilation process.\nThe comparison of both processes support a between-category assimilation process, where the sample size adjusts to the counter category's variability. This novel focus sheds light on between-category dynamics, providing valuable insights into the mechanisms of category learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Concepts and categories; Learning; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9wc588wh",
            "frozenauthors": [
                {
                    "first_name": "Ann-Katrin",
                    "middle_name": "",
                    "last_name": "Hosch",
                    "name_suffix": "",
                    "institution": "University of Bremen",
                    "department": ""
                },
                {
                    "first_name": "Janina",
                    "middle_name": "A",
                    "last_name": "Hoffmann",
                    "name_suffix": "",
                    "institution": "University of Bath",
                    "department": ""
                },
                {
                    "first_name": "Bettina",
                    "middle_name": "",
                    "last_name": "von Helversen",
                    "name_suffix": "",
                    "institution": "University of Bremen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21704/galley/11303/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21704/galley/22097/download/"
                }
            ]
        },
        {
            "pk": 24019,
            "title": "CAUS: A Dataset for Question Generation based on Human Cognition Leveraging Large Language Models",
            "subtitle": null,
            "abstract": "We introduce the Curious About Uncertain Scene (CAUS) dataset, designed to enable Large Language Models, specifically GPT-4, to emulate human cognitive processes for resolving uncertainties. Leveraging this dataset, we investigate the potential of LLMs to engage in questioning effectively. Our approach involves providing scene descriptions embedded with uncertainties to stimulate the generation of reasoning and queries. The queries are then classified according to multi-dimensional criteria. All procedures are facilitated by a collaborative system involving both LLMs and human researchers. Our results demonstrate that GPT-4 can effectively generate pertinent questions and grasp their nuances, particularly when given appropriate context and instructions. The study suggests that incorporating human-like questioning into AI models improves their ability to manage uncertainties, paving the way for future advancements in Artificial Intelligence (AI).",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Psychology; Human Factors; Learning; Computer-based experiment"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6522j4p0",
            "frozenauthors": [
                {
                    "first_name": "Minjung",
                    "middle_name": "",
                    "last_name": "Shin",
                    "name_suffix": "",
                    "institution": "Seoul National University",
                    "department": ""
                },
                {
                    "first_name": "Donghyun",
                    "middle_name": "",
                    "last_name": "Kim",
                    "name_suffix": "",
                    "institution": "Dongguk university",
                    "department": ""
                },
                {
                    "first_name": "Jeh-Kwang",
                    "middle_name": "",
                    "last_name": "Ryu",
                    "name_suffix": "",
                    "institution": "Dongguk University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24019/galley/13613/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24019/galley/20980/download/"
                }
            ]
        },
        {
            "pk": 24465,
            "title": "Causal coherence improves episodic memory of dynamic events",
            "subtitle": null,
            "abstract": "“Episodes” in memory are formed by the experience of dynamic events that unfold over time. However, just because a series of events unfolds sequentially does not mean that its constituents are related. Sequences can have a high degree of causal coherence, each event connecting to the next through a cause-and-effect relationship, or be a fragmented series of unrelated occurrences. Are causally coherent events remembered better? We used dynamic stimuli showing unfamiliar events to test the effect of causal structure on episodic recall in a cued memory task. Experiment 1 found that the order of causally coherent sequences of events is better remembered than that of fragmented events. Experiment 2 showed that recall of causally relevant details of coherent stimuli is superior to recall of details in fragmented sequences. These findings demonstrate that the episodic memory system is sensitive to the causal structure of events and suggest coherence usually improves recall.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Causal reasoning; Event cognition; Memory"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/248493jk",
            "frozenauthors": [
                {
                    "first_name": "Andreas",
                    "middle_name": "",
                    "last_name": "Arslan",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "F.",
                    "last_name": "Kominsky",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24465/galley/14062/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24465/galley/20981/download/"
                }
            ]
        },
        {
            "pk": 21660,
            "title": "Causal inferencing relies on domain-specific systems: Evidence from illness causality",
            "subtitle": null,
            "abstract": "Our remarkable ability to infer complex cause-effect relationships is thought to distinguish humans from all other species. Despite that causal inferencing pervades human cognition, it remains unclear whether this fundamental cognitive ability is supported by a unified, domain-general mechanism or multiple domain-specific mechanisms. Both the language and logical reasoning systems have been described as possible unified substrates of causal inferencing. The current study uses neuroimaging to offer insight into this debate. We specifically focus on the culturally universal and highly motivationally relevant case of inferring illness causes. Participants read causal and noncausal vignettes about illness and mechanical failure while undergoing fMRI. We find that inferring the causes of illness selectively activates the brain's ‘animacy network,' particularly the precuneus. By contrast, a domain-general (i.e., ‘content-invariant') preference for causal inferencing did not emerge, including in the language and logical reasoning networks. Together, this evidence suggests that domain-specific mechanisms enable causal inferencing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Causal reasoning; Concepts and categories; Language understanding; fMRI"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1nd044x4",
            "frozenauthors": [
                {
                    "first_name": "Miriam",
                    "middle_name": "",
                    "last_name": "Hauptman",
                    "name_suffix": "",
                    "institution": "Johns Hopkins University",
                    "department": ""
                },
                {
                    "first_name": "Marina",
                    "middle_name": "",
                    "last_name": "Bedny",
                    "name_suffix": "",
                    "institution": "Johns Hopkins University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21660/galley/11259/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21660/galley/14568/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21660/galley/22014/download/"
                }
            ]
        },
        {
            "pk": 24251,
            "title": "Causal Information Seeking",
            "subtitle": null,
            "abstract": "How do people's causal knowledge influence how they seek information? The current work tasks participants with choosing to observe disease symptoms in a setting where they know a disease's etiology and related symptoms. We use causal graphical models (CGMs) to formalize their causal knowledge of the disease, and find that people tend to use their expected information gain, computed over their CGM-generated probability beliefs, to search for information in causal settings.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Causal reasoning; Reasoning; Bayesian modeling; Knowledge representation"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0s44w06b",
            "frozenauthors": [
                {
                    "first_name": "Brian",
                    "middle_name": "N",
                    "last_name": "Yin",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Bob",
                    "middle_name": "",
                    "last_name": "Rehder",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24251/galley/13847/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24251/galley/20982/download/"
                }
            ]
        },
        {
            "pk": 24698,
            "title": "Causation on a continuum: normality effects on causal judgments",
            "subtitle": null,
            "abstract": "Imagine that a river becomes polluted if two plants generate too much waste. One might be more inclined to say that a plant caused the river to become polluted when it produced more waste than expected. While similar normality effects on causal judgments have been observed in cases with binary variables, little work has focused on cases with continuous variables. To test whether the statistical normality of continuous variables influences causal judgments, we had participants learn statistical norms over repeated iterations of a vignette and make a causal judgment about an instance of that vignette. Following Icard et al. (2017), we manipulated the causal structure and the normality of each cause. By testing whether normality effects on causal judgment generalize to cases with continuous variables, our results help determine whether these effects are central to human cognition, or simply apply to a subset of cases studied thus far.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Philosophy; Psychology; Causal reasoning; Statistical learning; Computational Modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5bc9b8zp",
            "frozenauthors": [
                {
                    "first_name": "Kaylee",
                    "middle_name": "",
                    "last_name": "Miceli",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                },
                {
                    "first_name": "Nina",
                    "middle_name": "",
                    "last_name": "Van Rooy",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                },
                {
                    "first_name": "Kevin",
                    "middle_name": "",
                    "last_name": "O'Neill",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                },
                {
                    "first_name": "Felipe",
                    "middle_name": "",
                    "last_name": "DeBrigard",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24698/galley/20983/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24698/galley/14296/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24698/galley/18131/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24698/galley/20983/download/"
                }
            ]
        },
        {
            "pk": 24431,
            "title": "Chain Versus Common Cause: Biased Causal Strength Judgments in Humans and Large Language Models",
            "subtitle": null,
            "abstract": "Causal reasoning is important for humans and artificial intelligence (AI). Causal Bayesian Networks (CBNs) model causal relationships using directed links between nodes in a network. Deviations from their edicts result in biased judgments. This study explores one such bias by examining two structures in CBNs: canonical Chain (A→C→B) and Common Cause (A←C→B) networks. In these structures, if C is known, the probability of the outcome (B) is normatively independent of the initial cause (A). But humans often ignore the independence. We tested mutually exclusive predictions of three theories that could account for this bias (N=300). Our results show that humans perceive causes in Chain structures as significantly stronger, supporting only one of the hypotheses. The increased perceived causal power might reflect a view of intermediate causes as more reflective of reliable mechanisms. The bias may stem from our interventions or how we talk about causality with others. LLMs are primarily trained on language data. Therefore, examining whether they exhibit similar biases can determine the extent to which language is the vehicle of such causal biases, with implications for whether LLMs can abstract causal principles. We, therefore, subjected three LLMs, GPT3.5-Turbo, GPT4, and Luminous Supreme Control, to the same queries as our human subjects, adjusting a key ‘temperature' hyperparameter. We show that at greater randomness levels, LLMs exhibit a similar bias, suggesting it is supported by language use. The absence of item effects suggests a degree of causal principle abstraction in LLMs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Computer Science; Psychology; Behavioral Science; Causal reasoning; Language and thought; Reasoning; Computer-based experiment; Large Language Models; Statistics; Survey"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2w45f1bv",
            "frozenauthors": [
                {
                    "first_name": "Anita",
                    "middle_name": "",
                    "last_name": "Keshmirian",
                    "name_suffix": "",
                    "institution": "Forward College",
                    "department": ""
                },
                {
                    "first_name": "Moritz",
                    "middle_name": "",
                    "last_name": "Willig",
                    "name_suffix": "",
                    "institution": "Technical University of Darmstadt",
                    "department": ""
                },
                {
                    "first_name": "Babak",
                    "middle_name": "",
                    "last_name": "Hemmatian",
                    "name_suffix": "",
                    "institution": "University of Illinois Urbana-Champaign",
                    "department": ""
                },
                {
                    "first_name": "Kristian",
                    "middle_name": "",
                    "last_name": "Kersting",
                    "name_suffix": "",
                    "institution": "TU Darmstadt",
                    "department": ""
                },
                {
                    "first_name": "Ulrike",
                    "middle_name": "",
                    "last_name": "Hahn",
                    "name_suffix": "",
                    "institution": "Birkbeck, University of London",
                    "department": ""
                },
                {
                    "first_name": "Tobias",
                    "middle_name": "",
                    "last_name": "Gerstenberg",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24431/galley/14028/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24431/galley/20984/download/"
                }
            ]
        },
        {
            "pk": 24500,
            "title": "Challenges for a computational explanation of flexible linguistic inference",
            "subtitle": null,
            "abstract": "We identify theoretical challenges for developing a computational explanation of flexible linguistic inference. Specifically, the human ability to interpret a novel linguistic expression (like “mask-shaming”), where inferring plausible meanings requires integrating relevant background knowledge (e.g., COVID-19 pandemic). We lay out (i) the core properties of the phenomenon that together make up our construal of the explanandum, (ii) explanatory desiderata to help make sure a theory explains the explanandum, and (iii) cognitive constraints to ensure a theory can be plausibly realised by human cognition and the brain. By doing so, we lay bare the ‘force field' that theories of this explanandum have to navigate, and we give examples of tensions that arise between different components of this force field. This is an important step in theory-development because it allows researchers who aim to solve one part of the puzzle of flexible linguistic inference to keep in clear view the other parts.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language understanding; Computational Modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6wz0t6bv",
            "frozenauthors": [
                {
                    "first_name": "Marieke",
                    "middle_name": "",
                    "last_name": "Woensdregt",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Mark",
                    "middle_name": "",
                    "last_name": "Blokpoel",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Iris",
                    "middle_name": "",
                    "last_name": "van Rooij",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Andrea",
                    "middle_name": "E",
                    "last_name": "Martin",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Psycholinguistics",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24500/galley/20985/download/"
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            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24500/galley/14097/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24500/galley/20985/download/"
                }
            ]
        },
        {
            "pk": 21470,
            "title": "Challenging the control-of-variables strategy: How confounded comparisons can support children's science learning",
            "subtitle": null,
            "abstract": "The control-of-variables strategy is often considered to be the superior strategy when children learn from experiments. However, by simulating Bayesian likelihoods of outcomes from a water displacement task, we show that certain confounded comparisons may support belief revision better than controlled comparisons. We tested this assumption by experimentally varying the types of comparisons that participants observed in a learning task involving balls of different sizes and materials (N = 90, age range 6- to 9-yrs). In the Size, Material, and Mixed conditions we presented controlled comparisons. In the Confounded Incongruent Condition, we presented confounded comparisons in which the larger ball was made of the heavier material. In line with our hypotheses, children in the Confounded Incongruent Condition revised their beliefs more than children in the other conditions, as indicated by higher transfer test scores. These findings suggest that confounded comparisons may in fact sometimes provide more optimal information for learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Causal reasoning; Bayesian modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/42c70920",
            "frozenauthors": [
                {
                    "first_name": "Lucas",
                    "middle_name": "",
                    "last_name": "Lörch",
                    "name_suffix": "",
                    "institution": "DIPF Leibniz Institute for Research and Information in Education",
                    "department": ""
                },
                {
                    "first_name": "Elizabeth",
                    "middle_name": "",
                    "last_name": "Bonawitz",
                    "name_suffix": "",
                    "institution": "Harvard",
                    "department": ""
                },
                {
                    "first_name": "Garvin",
                    "middle_name": "",
                    "last_name": "Brod",
                    "name_suffix": "",
                    "institution": "DIPF Leibniz Institute for Research and Information in Education",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21470/galley/11069/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21470/galley/21915/download/"
                }
            ]
        },
        {
            "pk": 24282,
            "title": "Changes in Partner Models – Effects of Adaptivity in the Course of Explanations",
            "subtitle": null,
            "abstract": "The process of adaptation to the partner in the course of an interaction is still not well understood. In the case of explanatory dialogues, to provide satisfying explanations, explainers have to consider the needs of the explainees. This requires mental representations of the explainees, i.e., “partner models”. Little is known about whether and how modifications of partner models during an explanation take place. We assumed that they get informed by the interactive behaviour of the explainee and investigated partner models in relation to explainees' verbal moves. A total of 59 dyadic explanations were investigated in an observation study. The comparison of the partner models before and after the explanation showed changes regarding, e.g., knowledge, interest in the explanation, cooperation, and mood. Moves such as questions as well as summarising and paraphrasing information given by the explainees were associated with the partner model dimensions interest in the explanation and co-construction.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Interactive behavior; Representation; Verbal protocol studies"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5bb7p5pt",
            "frozenauthors": [
                {
                    "first_name": "Heike",
                    "middle_name": "M.",
                    "last_name": "Buhl",
                    "name_suffix": "",
                    "institution": "Paderborn University",
                    "department": ""
                },
                {
                    "first_name": "Josephine Beryl",
                    "middle_name": "",
                    "last_name": "Fisher",
                    "name_suffix": "",
                    "institution": "University Paderborn",
                    "department": ""
                },
                {
                    "first_name": "Katharina",
                    "middle_name": "",
                    "last_name": "Rohlfing",
                    "name_suffix": "",
                    "institution": "Paderborn University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24282/galley/13878/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24282/galley/20986/download/"
                }
            ]
        },
        {
            "pk": 24385,
            "title": "Changes of self-others relation by synchronizing facial expressions",
            "subtitle": null,
            "abstract": "In our study, we address conflicts between individuals and groups, such as cyberbully on social media, as a challenge related to the distinction between the self and others. To address this issue using technology, we propose the concept of introducing facial synchronization in the virtual realm as a means to manipulate the boundary between oneself and others.\nWe designed an experiment using Cyberball that simulates an ostracism environment, effectively partitioning the boundary between the self and others. This task was conducted in Virtual Reality (VR), with the agent's facial expressions synchronized with those of the participant.\nOur findings indicated a reduction in feelings of alienation within the ostracism environment. This discovery has potential implications for communication media, particularly in enhancing interfaces for individuals who may experience exclusionary behavior on social media.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Emotion; Emotion Perception; Human-computer interaction; Mood; Social cognition"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6s93s6p6",
            "frozenauthors": [
                {
                    "first_name": "Ryunosuke",
                    "middle_name": "",
                    "last_name": "Baba",
                    "name_suffix": "",
                    "institution": "Shizuoka University",
                    "department": ""
                },
                {
                    "first_name": "Junya",
                    "middle_name": "",
                    "last_name": "Morita",
                    "name_suffix": "",
                    "institution": "Shizuoka University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24385/galley/13982/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24385/galley/20987/download/"
                }
            ]
        },
        {
            "pk": 24420,
            "title": "Channel-adaptive Graph Convolution based Temporal Encoder Network for EEG Emotion Recognition",
            "subtitle": null,
            "abstract": "Brain-computer interface technology has made significant progress in the field of intelligent human-computer interaction. Among them, electroencephalography-based emotion recognition, as one of the important research directions in emotional brain-computer interaction, has received widespread attention. However, most previous studies were limited to feature extraction of global brain networks and local brain areas in the EEG spatial domain but ignored the channel-level dynamic features of EEG. To address this limitation, we proposed a Channel-Adaptive Graph Convolutional Network with Temporal Encoder (CAG-TEN). In CAG-TEN, the channel-adaptive graph convolutional module assigns a unique parameter space to each channel, focusing on channel-level dynamic features. Additionally, the temporal encoder module, inspired by the Encoders concept, is used to explore long-term temporal dependencies in EEG sequences. We conduct rigorous comparative experiments of CAG-TEN against several representative baseline models on the SEED dataset and achieve optimal performance.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Emotion; Emotion Perception; Electroencephalography (EEG)"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2hw937kk",
            "frozenauthors": [
                {
                    "first_name": "Renxi",
                    "middle_name": "",
                    "last_name": "Guo",
                    "name_suffix": "",
                    "institution": "Nanchang University",
                    "department": ""
                },
                {
                    "first_name": "Hong",
                    "middle_name": "",
                    "last_name": "Rao",
                    "name_suffix": "",
                    "institution": "Nanchang University",
                    "department": ""
                },
                {
                    "first_name": "Panfeng",
                    "middle_name": "",
                    "last_name": "An",
                    "name_suffix": "",
                    "institution": "Shanghai Jiaotong University",
                    "department": ""
                },
                {
                    "first_name": "Wenying",
                    "middle_name": "",
                    "last_name": "Duan",
                    "name_suffix": "",
                    "institution": "School of Mathematics and Computer Sciences",
                    "department": ""
                },
                {
                    "first_name": "Shengbo",
                    "middle_name": "",
                    "last_name": "Chen",
                    "name_suffix": "",
                    "institution": "Henan University",
                    "department": ""
                },
                {
                    "first_name": "Gang",
                    "middle_name": "",
                    "last_name": "Luo",
                    "name_suffix": "",
                    "institution": "Nanchang University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24420/galley/14017/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24420/galley/20988/download/"
                }
            ]
        },
        {
            "pk": 24578,
            "title": "Characteristic of persistently active neurons in the human Medial Temporal Lobe during Working Memory maintenance",
            "subtitle": null,
            "abstract": "Working memory (WM) is an essential component of cognition, believed to be involved in several cognitive processes. Persistent neural activity (PNA) during WM maintenance has been widely reported. In this study we tested whether stimulus-selectivity constited a predictor of increased PNA during WM maintenance. We performed single-cell recordings on medial temporal lobe (MTL) neurons and measured PNA during encoding and maintenance. We identified image-selective neurons, based on the observed firing rate (FR) elicited by exposure to different images. We compared the FR of such neurons during encoding and maintenance when the maintaining the prefered image in WM with the FR for maintenance of a non-preferred image. We observed PNA for both conditions, and measured a higher FR during maintenance of the preferred image. In alignment with the existing literature, the results of our analysis suggest that stimulus-selectivity is a potential predictor of PNA during WM maintenance.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Memory; Single-cell recording"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/20w7205f",
            "frozenauthors": [
                {
                    "first_name": "Ruben",
                    "middle_name": "Alexandre",
                    "last_name": "Castro",
                    "name_suffix": "",
                    "institution": "University of Warsaw",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24578/galley/20989/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24578/galley/14175/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24578/galley/20989/download/"
                }
            ]
        },
        {
            "pk": 24573,
            "title": "Characterizing Age-Related Change in Learning the Value of Cognitive Effort",
            "subtitle": null,
            "abstract": "To behave efficiently, individuals must decide when to exert cognitive effort by weighing its benefits and costs. While adults often make such economical choices, less is known about how these decisions develop. Here, we tested whether children and adolescents (N=150, 10-20 years) also learn about the value of cognitive effort during a task-switching experiment manipulating the reward benefits (higher vs. lower incentives) and difficulty costs (easy vs. hard conditions) of engaging cognitive effort. Mixed-effects modeling analyses examining the influences of age, learning over time, and the reward and difficulty manipulations on task-switching performance revealed that accuracy improved significantly more rapidly for higher than lower incentives with increasing age, especially during the beginning and middle of learning. Meanwhile, accuracy improved marginally more rapidly for the easy than hard condition with increasing age. Together, these results suggest that reward and difficulty information distinctly guide cognitive effort across time and age.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Decision making; Learning; Computer-based experiment"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0k77p9n7",
            "frozenauthors": [
                {
                    "first_name": "Camille",
                    "middle_name": "V",
                    "last_name": "Phaneuf",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Isabelle",
                    "middle_name": "M",
                    "last_name": "Jacques",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Catherine",
                    "middle_name": "",
                    "last_name": "Insel",
                    "name_suffix": "",
                    "institution": "Columbia University",
                    "department": ""
                },
                {
                    "first_name": "Catherine",
                    "middle_name": "",
                    "last_name": "Insel",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "A. Ross",
                    "middle_name": "",
                    "last_name": "Otto",
                    "name_suffix": "",
                    "institution": "McGill University",
                    "department": ""
                },
                {
                    "first_name": "Leah",
                    "middle_name": "",
                    "last_name": "Somerville",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Leah",
                    "middle_name": "",
                    "last_name": "Somerville",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24573/galley/20990/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24573/galley/14170/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24573/galley/20990/download/"
                }
            ]
        },
        {
            "pk": 24415,
            "title": "Characterizing Contextual Variation in Children's Preschool Language Environment Using Naturalistic Egocentric Videos",
            "subtitle": null,
            "abstract": "What structures children's early language environment? Large corpora of child-centered naturalistic recordings provide an important window into this question, but most available data centers on young children within the home or in lab contexts interacting primarily with a single caregiver. Here, we characterize children's language experience in a very different kind of environment: the preschool classroom. Children ages 3 – 5 years (N = 26) wore a head-mounted camera in their preschool class, yielding a naturalistic, egocentric view of children's everyday experience across many classroom activity contexts (e.g., sand play, snack time), with >30 hours of video data. Using semi-automatic transcriptions (227,624 words), we find that activity contexts in the preschool classroom vary in both the quality and quantity of the language that children both hear and produce. Together, these findings reinforce prior theories emphasizing the contribution of activity contexts in structuring the variability in children's early learning environments.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive development; Language development; Language learning; Classroom studies; Corpus studies"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/94j9m5v1",
            "frozenauthors": [
                {
                    "first_name": "Robert",
                    "middle_name": "Z.",
                    "last_name": "Sparks",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Bria",
                    "middle_name": "",
                    "last_name": "Long",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Grace",
                    "middle_name": "E",
                    "last_name": "Keene",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Malia",
                    "middle_name": "J.",
                    "last_name": "Perez",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Alvin",
                    "middle_name": "Wei Ming",
                    "last_name": "Tan",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Virginia",
                    "middle_name": "A",
                    "last_name": "Marchman",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "C.",
                    "last_name": "Frank",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24415/galley/14012/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24415/galley/20991/download/"
                }
            ]
        },
        {
            "pk": 24173,
            "title": "ChatGPT and the Illusion of Explanatory Depth",
            "subtitle": null,
            "abstract": "The recent surge in the use of AI-powered chatbots such as ChatGPT has led to new challenges in academia. These chatbots can enable student plagiarism and the submission of misleading content, undermining educational objectives. With plagiarism detectors unreliable in the face of this issue, educational institutions have been struggling to update their policies apace. This study assesses the effectiveness of sending warning messages - a common strategy used to discourage unethical use of ChatGPT - and investigates the use of the illusion of explanatory depth (IOED) paradigm as an alternative intervention. An international sample of students was asked to rate their understanding of, likelihood to use, and moral stance toward ChatGPT-generated text in assignments both before and after either reading a cautionary university message or explaining how ChatGPT works. Results showed that the explanation task did lead to the expected reduction in ratings of understanding, but despite this, neither moral acceptability nor likelihood to use decreased along with it. Similarly, reading the cautionary message neither resulted in a change in likelihood to use nor in moral acceptability, although it unexpectedly increased ratings of understanding. The results suggest that tackling students' understanding of ChatGPT is insufficient when it comes to deterring its unethical use, and that future interventions might want to have students reflect on moral issues surrounding the use of AI-powered chatbots.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Education; Psychology; Externally-supported cognition; Human-computer interaction"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2m38s5xm",
            "frozenauthors": [
                {
                    "first_name": "Yomn",
                    "middle_name": "",
                    "last_name": "Elsayed",
                    "name_suffix": "",
                    "institution": "Erasmus University Rotterdam",
                    "department": ""
                },
                {
                    "first_name": "Steven",
                    "middle_name": "",
                    "last_name": "Verheyen",
                    "name_suffix": "",
                    "institution": "Erasmus University Rotterdam",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24173/galley/13769/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24173/galley/20992/download/"
                }
            ]
        },
        {
            "pk": 21506,
            "title": "Child-Caregiver Gaze Dynamics in Naturalistic Face-to-Face Conversations",
            "subtitle": null,
            "abstract": "This study examines the development of children's gaze during face-to-face conversations, following up on previous work suggesting a protracted development in attending to the interlocutor's face. Using recent mobile eye-tracking technology, we observed children interacting with their parents at home in natural settings. In contrast to previous work, we found that children, even in early middle childhood, exhibit adult-like gaze patterns toward the interlocutor. However, differences emerge in gaze allocation between speaking and listening roles, indicating that while children may focus on faces similarly to adults, their use of gaze for social signaling, such as turn-taking cues, may still be maturing. The work underscores the critical role of social context in understanding the development of non-verbal behavior in face-to-face conversation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive development; Development; Eye tracking"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/141609kq",
            "frozenauthors": [
                {
                    "first_name": "Dhia Elhak",
                    "middle_name": "",
                    "last_name": "Goumri",
                    "name_suffix": "",
                    "institution": "Aix-Marseille Univesité",
                    "department": ""
                },
                {
                    "first_name": "Leonor",
                    "middle_name": "",
                    "last_name": "Becerra-Bonache",
                    "name_suffix": "",
                    "institution": "Aix-Marseille University",
                    "department": ""
                },
                {
                    "first_name": "Abdellah",
                    "middle_name": "",
                    "last_name": "Fourtassi",
                    "name_suffix": "",
                    "institution": "Aix-Marseille University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21506/galley/11105/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21506/galley/21951/download/"
                }
            ]
        },
        {
            "pk": 21475,
            "title": "Children and Adults Consider Others' Resources When Inferring Their Emotions",
            "subtitle": null,
            "abstract": "The amount of resources someone has can influence their emotional responses to events. Two preregistered experiments investigated whether adults and children consider others' resource quantities when inferring their emotions. Sixty adults (Experiment 1) and 135 8-10-year-olds (Experiment 2) saw stories about people wanting an item but differing in the number of items they have enough money to buy (ranging from 1 to 5). Participants rated how these people felt both when buying the item and when losing it. Both adults and children judged that the fewer resources someone has, the sadder they felt  when the item was lost, and the bigger emotional change they experienced (relative to when buying the item). Adults also judged that the impact of resource scarcity on emotion was most significant when the person had depleted all their resources, as opposed to still retaining some to influence the negative outcome, and this pattern is emerging in children. These findings suggest that even when the same negative event occurs, adults and children as young as 8 consider others' available resources when inferring their emotional responses to the event.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Development; Emotion; Social cognition"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/04d4j2qh",
            "frozenauthors": [
                {
                    "first_name": "Tiffany",
                    "middle_name": "",
                    "last_name": "Doan",
                    "name_suffix": "",
                    "institution": "University of Toronto, Scarborough",
                    "department": ""
                },
                {
                    "first_name": "Yang",
                    "middle_name": "",
                    "last_name": "Wu",
                    "name_suffix": "",
                    "institution": "University of Toronto Scarborough",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21475/galley/11074/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21475/galley/21920/download/"
                }
            ]
        },
        {
            "pk": 21601,
            "title": "Children can use distributional cues to acquire recursive structures",
            "subtitle": null,
            "abstract": "While the ability of recursion is considered universally available, there are considerable cross- and with-linguistic differences regarding the rules for recursive embedding, which must be learned from language-specific experience. One proposal argues that the recursivity of a structure is learnable as a productive generalization from distributional information in non-embedded input, and adults can indeed use such distributional cues to acquire recursive structures in an artificial language. However, it is not yet known whether children can use distributional information in this way. In this work, we examine children's distributional learning of recursive structures. We exposed children to non-embedded sentences in an artificial grammar, where we manipulated the productivity of the structure across conditions. At test, we found that children exposed to productive input were more likely to accept recursively embedded sentences unattested during the exposure phase. The results suggest that children can make use of distributional information to acquire recursive structures.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language development; Language learning; Statistical learning; Syntax"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3d52v78v",
            "frozenauthors": [
                {
                    "first_name": "Daoxin",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                },
                {
                    "first_name": "Kathryn",
                    "middle_name": "",
                    "last_name": "Schuler",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21601/galley/11200/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21601/galley/21994/download/"
                }
            ]
        },
        {
            "pk": 24175,
            "title": "Children expect adults to hold gender stereotypes, even when they are not accurate",
            "subtitle": null,
            "abstract": "Gender stereotypes are early-emerging and harmful for young children. However, it is unclear how children reason about other people's gender stereotypes, especially when they differ from children's own beliefs. Across two preregistered experiments (total n=271), we tested whether 5- to 7-year-old children expect teachers to give engineering games to boy students and story games to girl students, even when children themselves know that these are not students' true preferences. Experiment 1 found that participants were more likely to predict that a teacher would give students stereotypical games when the teacher did not know (versus did know) the students' true counter-stereotypical interests. In Experiment 2, when the students expressed interest in both games, 6- and 7-year-olds selectively predicted that teachers would give students whom they had just met stereotypical games. Thus, by the time children enter school, they think that adults hold gender stereotypes, even if children know these stereotypes are inaccurate, which may impact children's learning and decision-making in the classroom.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Social cognition; Theory of Mind"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7q01r7sx",
            "frozenauthors": [
                {
                    "first_name": "Mika",
                    "middle_name": "",
                    "last_name": "Asaba",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Marianna",
                    "middle_name": "Y.",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Julia",
                    "middle_name": "Anne",
                    "last_name": "Leonard",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24175/galley/13771/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24175/galley/20993/download/"
                }
            ]
        },
        {
            "pk": 21463,
            "title": "Children Expect People to Accurately Represent the Minds of Their Close Social Partners",
            "subtitle": null,
            "abstract": "Do children reason that people in close relationships accurately represent each other's minds? In two experiments (total N = 123), we found that 7- to 9-year-old children from the US (i) reason that people who are close will accurately represent each other's goals and desires and (ii) infer that people are socially close when they accurately predict each other's emotional states. These findings suggest that children reason flexibly about mental state attributions within close relationships.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Social cognition; Theory of Mind; Developmental analysis"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/75m9c4b3",
            "frozenauthors": [
                {
                    "first_name": "Brandon",
                    "middle_name": "Matthew",
                    "last_name": "Woo",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Emma",
                    "middle_name": "",
                    "last_name": "Yu",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Ashley",
                    "middle_name": "J",
                    "last_name": "Thomas",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21463/galley/11062/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21463/galley/21908/download/"
                }
            ]
        },
        {
            "pk": 21386,
            "title": "Children's Emerging Ability to Balance Internal and External Cognitive Resources",
            "subtitle": null,
            "abstract": "Humans have increasing opportunities to offload internal cognitive demand, such as by setting reminders to aid future memory performance. Here, we examine how children begin to balance mind and world: weighing up when to offload cognition and when to rely on their unaided capacities. Australian children aged 6 to 9 years (N = 120) were tasked with remembering the locations of 1, 3, 5, and 7 targets hidden under 25 cups. In the critical test phase, children were provided with a limited number of ‘tokens' to distribute across trials, which they could use to mark target locations and assist future performance. Following the final search period, children were invited to evaluate and adjust their initial allocation. Results showed that 8- to 9-year-olds prospectively allocated proportionately more tokens to difficult trials, whereas 6- to 7-year-olds did so only in retrospect. Throughout childhood, humans become increasingly adept at balancing internal and external cognition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Externally-supported cognition; Memory; Developmental analysis; Statistics"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5c49p1dk",
            "frozenauthors": [
                {
                    "first_name": "Lily",
                    "middle_name": "S",
                    "last_name": "Dicken",
                    "name_suffix": "",
                    "institution": "University of Queensland",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "",
                    "last_name": "Suddendorf",
                    "name_suffix": "",
                    "institution": "University of Queensland",
                    "department": ""
                },
                {
                    "first_name": "Adam",
                    "middle_name": "",
                    "last_name": "Bulley",
                    "name_suffix": "",
                    "institution": "The Behavioural Insights Team",
                    "department": ""
                },
                {
                    "first_name": "Muireann",
                    "middle_name": "",
                    "last_name": "Irish",
                    "name_suffix": "",
                    "institution": "The University of Sydney",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Redshaw",
                    "name_suffix": "",
                    "institution": "University of Queensland",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21386/galley/10985/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21386/galley/21831/download/"
                }
            ]
        },
        {
            "pk": 21558,
            "title": "Children's Expectations About Epistemic Change",
            "subtitle": null,
            "abstract": "People's mental states constantly change as they navigate and interact with their environment. Accordingly, social reasoning requires us not only to represent mental states but also to understand the ways in which mental states tend to change. Despite their importance, relatively little is known about children's understanding of the dynamics of mental states. To explore this question, we studied a common type of mental state change: knowledge gain. Specifically, we studied whether five- and six-year-olds distinguish between agents who gain knowledge and those who lose knowledge. In one condition, children saw an agent answer a two-alternative choice question incorrectly, followed by an identical-looking agent who answered the same question correctly (i.e., gaining knowledge). In another condition, children saw the reverse pattern (i.e., losing knowledge). Children were more likely to infer they had seen two different agents in the knowledge loss condition relative to the knowledge gain condition. These results suggest that children have intuitions about how epistemic states change and open new questions about children's naive theories of mental state dynamics.",
            "language": null,
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Social cognition; Theory of Mind"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1dc9n7zh",
            "frozenauthors": [
                {
                    "first_name": "Mack",
                    "middle_name": "",
                    "last_name": "Briscoe",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Rui",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Julian",
                    "middle_name": "",
                    "last_name": "Jara-Ettinger",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21558/galley/11157/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21558/galley/14634/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21558/galley/20999/download/"
                }
            ]
        },
        {
            "pk": 24625,
            "title": "Children's multimodal coordination during collaborative problem solving",
            "subtitle": null,
            "abstract": "When children solve cognitive problems together, they coordinate their speech, hand movements and head movements. Previous studies with adults have shown that such multimodal coordination is related to better collaboration. We do not know whether this is true for children, however. In this study, dyads of children (6-10 years) discussed and solved balance scale problems together. To investigate children's multimodal coordination, we measured their speech, hand movements and head movements throughout their bouts of discussion, and applied multidimensional Recurrence Quantification Analysis (MdRQA) on these timeseries. We coded the type of collaboration the children engaged in during these bouts of discussion. We measured performance regarding predicting to which side the balance scale would tilt. We will analyse how children's multimodal coordination is related to the type of collaboration and to their performance on the balance scale problems. Our results will show how successful collaboration between children emerges from their multimodal coordination.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive development; Complex systems; Dynamical Systems; Problem Solving; Gesture analysis"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2r98p9kt",
            "frozenauthors": [
                {
                    "first_name": "Lisette",
                    "middle_name": "",
                    "last_name": "De Jonge-Hoekstra",
                    "name_suffix": "",
                    "institution": "Psychology, Faculty of Behavioral and Social Sciences, University of Groningen",
                    "department": ""
                },
                {
                    "first_name": "Wim",
                    "middle_name": "",
                    "last_name": "Pouw",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Steffie",
                    "middle_name": "",
                    "last_name": "van der Steen",
                    "name_suffix": "",
                    "institution": "Faculty of Behavioral and Social Sciences, University of Groningen",
                    "department": ""
                },
                {
                    "first_name": "Ralf F.A.",
                    "middle_name": "",
                    "last_name": "Cox",
                    "name_suffix": "",
                    "institution": "University of Groningen",
                    "department": ""
                },
                {
                    "first_name": "James",
                    "middle_name": "",
                    "last_name": "Dixon",
                    "name_suffix": "",
                    "institution": "University of Connecticut",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24625/galley/20998/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24625/galley/14222/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24625/galley/17993/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24625/galley/20998/download/"
                }
            ]
        },
        {
            "pk": 23984,
            "title": "Children spontaneously discover efficient sorting algorithms in a seriation task",
            "subtitle": null,
            "abstract": "Efficient algorithms can enhance problem-solving in many cognitive domains but can be difficult to discover and use. For example, classical studies of seriation suggest that children struggle to apply algorithmic strategies in a simple sorting problem. We investigate the spontaneous discovery of algorithmic solutions across development. We gave children a variant of the sorting problem with hidden object ranks. Children sort animated bunnies into the right order, from the shortest to the tallest, when the bunnies are standing behind a wall so their heights are not visible. Children performed far above chance on this difficult sorting task, potentially because higher demands in memory and reasoning incentivized strategic behaviors. Children independently discovered at least two efficient algorithmic solutions to the sorting problem, Selection sort and Shaker sort. This result suggests that children are far more competent at sorting tasks than previous research would suggest. Additionally, older children were more efficient sorters than younger children. This suggests that competent performance on sorting tasks improves throughout development.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Development; Problem Solving; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7tj838s0",
            "frozenauthors": [
                {
                    "first_name": "Huiwen Alex",
                    "middle_name": "",
                    "last_name": "Yang",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Bill",
                    "middle_name": "",
                    "last_name": "Thompson",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Celeste",
                    "middle_name": "",
                    "last_name": "Kidd",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/23984/galley/13578/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/23984/galley/20994/download/"
                }
            ]
        },
        {
            "pk": 24364,
            "title": "Children's unexpected inferences across knowledge types",
            "subtitle": null,
            "abstract": "Developmental psychologists have often turned to children to clarify understanding of functional and mechanistic cognition. Here, we investigate children's epistemic inferences of function – what a thing is for – and mechanism – how a thing works. Children, like adults, believe a mechanism-knower knows more than a function-knower (Study 1). Yet, unlike adults, children do not expect that a mechanism-knower is also more likely to know function than a function-knower is to know mechanism (Study 2). Children's experience of learning function and mechanism of complex systems sheds light on this asymmetry; Children who are taught just mechanism can infer the complementary function, but, interestingly, children who are taught just function can likewise infer the complementary mechanism (Study 3). This paper considers the nature of children's epistemic intuitions and whether those beliefs are reflective of children's learning experience.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Causal reasoning; Cognitive development; Development; Instruction and teaching"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5v6960kt",
            "frozenauthors": [
                {
                    "first_name": "Amanda",
                    "middle_name": "",
                    "last_name": "McCarthy",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Emma",
                    "middle_name": "",
                    "last_name": "Courtney",
                    "name_suffix": "",
                    "institution": "Cold Spring Harbor Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Frank",
                    "middle_name": "",
                    "last_name": "Keil",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24364/galley/13961/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24364/galley/21000/download/"
                }
            ]
        },
        {
            "pk": 24611,
            "title": "Children's visual attention when planning informative multimodal descriptions of object locations",
            "subtitle": null,
            "abstract": "Children frequently use under-informative expressions (e.g., Side) while describing Left-Right relations between objects but use gestures to disambiguate the relative locations of objects (Karadöller et al., 2022). Here we ask how children collect visual information about the spatial relations they express when planning such descriptions. Twenty Turkish-speaking 8-year-olds saw displays with four pictures of the same two objects in various spatial configurations. Target pictures described to a confederate depicted left-right relations (e.g., lemon left to box). Descriptions were coded whether they were informative in speech, informative with gesture, or under-informative. Children had more target fixations when planning (1) informative than under-informative descriptions (β=0.515, SE=0.131, p<0.001); (2) descriptions that are informative with gesture than informative in speech (β=-0.827, SE=0.171, p<0.001). Results extend previous literature showing that visual attention changes as a function of informativeness and the modality (Ünal et al., 2022) of the description for 8-year-old children.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Cognitive development; Embodied Cognition; Language development; Language Production; Spatial cognition; Eye tracking; Gesture analysis"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0qv1d08p",
            "frozenauthors": [
                {
                    "first_name": "Dilay",
                    "middle_name": "Z.",
                    "last_name": "Karadoller",
                    "name_suffix": "",
                    "institution": "Middle East Technical University",
                    "department": ""
                },
                {
                    "first_name": "Asli",
                    "middle_name": "",
                    "last_name": "Ozyurek",
                    "name_suffix": "",
                    "institution": "Donders Institute",
                    "department": ""
                },
                {
                    "first_name": "Ercenur",
                    "middle_name": "",
                    "last_name": "Ünal",
                    "name_suffix": "",
                    "institution": "Ōzyeƒüin University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24611/galley/17967/download/"
                }
            ]
        },
        {
            "pk": 24165,
            "title": "Children Track Probabilistic Information in Speech Differently from Adults",
            "subtitle": null,
            "abstract": "Language learning is a sophisticated process as learners need to detect and extract rich regularities embedded in the continuous speech inputs. Children, compared to adults, appear to learn languages more effortlessly. Nevertheless, early studies in implicit statistical learning revealed little developmental differences between children and adults. Recent work has found the speed of statistical learning in adults is associated with their neural sensitivity to probabilistic information in speech. It is not well understood, however, whether children share similar or different underlying neural processes for probabilistic information compared to adults. Specifically, are children similar to faster or slower adult statistical learners, or neither of them? In the current study, children aged between 5 and 12 completed a passive auditory oddball task, where they listened to syllables at different local and global frequency of occurrence. We used two neurophysiological measures, auditory mismatch responses (MMR) and late discriminative negativity (LDN) to compare children's sensitivity to distributional probabilities in speech with adults. We found that children were more sensitive to probabilistic information in speech inputs at both the local and the global level than both faster and slower adult statistical learners. Moreover, unlike adults who integrate probabilistic information across global and local hierarchies, children seem to process different levels of probabilistic information in parallel.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Cognitive development; Language development; Language learning; Electroencephalography (EEG)"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/89v6q66x",
            "frozenauthors": [
                {
                    "first_name": "Yi-Lun",
                    "middle_name": "",
                    "last_name": "Weng",
                    "name_suffix": "",
                    "institution": "University of Delaware",
                    "department": ""
                },
                {
                    "first_name": "Julie",
                    "middle_name": "",
                    "last_name": "Schneider",
                    "name_suffix": "",
                    "institution": "Louisiana State University",
                    "department": ""
                },
                {
                    "first_name": "Zhenghan",
                    "middle_name": "",
                    "last_name": "Qi",
                    "name_suffix": "",
                    "institution": "Northeastern University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24165/galley/13761/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24165/galley/20995/download/"
                }
            ]
        },
        {
            "pk": 24156,
            "title": "Children track variability in adult attention and plan interventions accordingly",
            "subtitle": null,
            "abstract": "Prior research has shown that children are highly responsive to adults' attention, benefit from its presence, and suffer in its absence. However, not much is known about the extent to which children track other's attention to third parties, or the extent to which children actively make decisions and plans to engage adults' attention. In Experiment 1, we looked at whether children (mean: 5;11 range: 4;0-7;11) distinguished attentive and distracted adults in a minimal contrast where attention to a third party (a puppet) was all that varied and the adults were otherwise matched on affect, contingent responding, and other cues. Six- and seven-year-olds but not younger children predicted that the puppets would prefer the attentive adults. In Experiment 2, we looked at whether children (mean: 5;11 range: 4;0-7;11) tracked the co-variation between an adult's attentiveness and a puppet's topics of conversation. We found that older, but not younger children chose the puppets' next topic according to what the co-variation data indicated would best engage the adults' attention. These results suggest that by ages six and seven, but not earlier, children track adults' attention even in third-party contexts and can plan interventions to engage adults' attention.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Attention; Cognitive development; Social cognition"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8cv3h8tr",
            "frozenauthors": [
                {
                    "first_name": "Shengyi",
                    "middle_name": "",
                    "last_name": "Wu",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Laura",
                    "middle_name": "",
                    "last_name": "Schulz",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24156/galley/13752/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24156/galley/20996/download/"
                }
            ]
        },
        {
            "pk": 24663,
            "title": "Children use positive prescriptive information when asked to predict random samples",
            "subtitle": null,
            "abstract": "Previous work has found that when adults are asked for \"the first thing that comes to mind\", they will provide something that falls between the descriptive average and the prescriptive ideal. In two experiments, we tested whether children would also be influenced by prescriptive information in their first-to-mind judgments, but also when they were asked to predict a randomly sampled item. In Experiment 1, providing information about whether being longer or shorter made a fictional tool better or worse led children to provide judgments that were biased toward the prescriptively 'best' tool, regardless of what they were asked for, while adults ignored prescriptive information when asked for a random sample. Experiment 2 replicated this result but further showed that the effect was specifically driven by information about which objects were prescriptively good, and did not also arise when the only salient information was about which objects were prescriptively bad.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Development; Representation"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/02f2g4zm",
            "frozenauthors": [
                {
                    "first_name": "Jonathan",
                    "middle_name": "F.",
                    "last_name": "Kominsky",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "",
                    "last_name": "Knobe",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Elizabeth",
                    "middle_name": "",
                    "last_name": "Bonawitz",
                    "name_suffix": "",
                    "institution": "Harvard Graduate School of Education",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24663/galley/20997/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24663/galley/14261/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24663/galley/18062/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24663/galley/20997/download/"
                }
            ]
        },
        {
            "pk": 24662,
            "title": "Chinese Character Network Structure Affects Processing of Single Chinese Characters",
            "subtitle": null,
            "abstract": "Mandarin Chinese has a logographic writing system consisting of characters (e.g., 朋 and 友) that are monosyllabic morphemes often combined to form words (i.e., 朋友, “friend”). The vast majority of Chinese words consists of two monosyllabic characters. This research describes the construction and properties of the Chinese character network and demonstrates how its network structure has implications for the lexical processing of Chinese characters through an analysis of Chinese megastudy data. Capitalizing on a database of over 25,000 double-character Chinese words, a network representation was created to represent how single characters are combined to form double-character Chinese words. Network measures such as degree and closeness centrality were retrieved from the network representation and included as predictors in a regression model to predict visual lexical decision performance of single Chinese characters. Network measures contributed additional variance beyond traditional variables such as number of strokes and character frequency.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Morphology; Reading; Statistics"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0sd0f0mh",
            "frozenauthors": [
                {
                    "first_name": "Cynthia",
                    "middle_name": "S.Q.",
                    "last_name": "Siew",
                    "name_suffix": "",
                    "institution": "National University of Singapore",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24662/galley/21002/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24662/galley/14260/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24662/galley/18060/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24662/galley/21002/download/"
                }
            ]
        },
        {
            "pk": 24459,
            "title": "Chinese Child-Directed Speech Is Faster and More Fluent Than Adult-Directed Speech",
            "subtitle": null,
            "abstract": "This study investigated the differences in speaking rate and fluency between child-directed speech (CDS) and adult-directed speech (ADS), as well as individual variations. We analyzed fluency measures (speaking rate, pausing, repairs, and repetitions) in a corpus of Chinese ADS and CDS. The speech data included forty mothers telling the same story to their 18- or 24-month-old children and an adult. Our findings revealed that: (1) CDS was generally more fluent than ADS, with fewer pauses. (2) There were no significant differences in speaking rate between CDS and ADS for short utterances, but CDS was significantly faster than ADS for longer utterances. (3) We observed age-related differences in speaking rate between 18 and 24 months in relation to utterance length. This suggests that Chinese CDS is not slower but can be faster than ADS. These findings highlight language-specific and individual variations in the temporal aspects of CDS.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language development"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8q87k4mr",
            "frozenauthors": [
                {
                    "first_name": "Mengru",
                    "middle_name": "",
                    "last_name": "Han",
                    "name_suffix": "",
                    "institution": "East China Normal University",
                    "department": ""
                },
                {
                    "first_name": "Lianghui",
                    "middle_name": "",
                    "last_name": "Yang",
                    "name_suffix": "",
                    "institution": "East China Normal University",
                    "department": ""
                },
                {
                    "first_name": "Yan",
                    "middle_name": "",
                    "last_name": "Gu",
                    "name_suffix": "",
                    "institution": "University of Essex",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24459/galley/14056/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24459/galley/21003/download/"
                }
            ]
        },
        {
            "pk": 24471,
            "title": "Choice Architecture Induces Distortions in Economic Values: a Test across Two Memory Elicitations",
            "subtitle": null,
            "abstract": "Here we present results from three experiments demonstrating that the way in which options are organized during learning (i.e., the choice architecture) significantly affects the resulting memory representations of their economic values. That is, options that are optimal in the learning contexts tend to be significantly overvalued in the follow-up memory tests. By changing the choice architecture of the learning phase across experiments, we were able to show that this irrational bias is a direct consequence of the learning choice architecture, since presenting options in all possible combinations during learning eradicates this effect. Critically, all the results stand irrespective of the memory elicitation used.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Learning; Memory"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3vm8v224",
            "frozenauthors": [
                {
                    "first_name": "Magdalena",
                    "middle_name": "",
                    "last_name": "Soukupova",
                    "name_suffix": "",
                    "institution": "Ecole Normale Superieure",
                    "department": ""
                },
                {
                    "first_name": "Stefano",
                    "middle_name": "",
                    "last_name": "Palminteri",
                    "name_suffix": "",
                    "institution": "École normale supérieure",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24471/galley/14068/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24471/galley/21004/download/"
                }
            ]
        },
        {
            "pk": 24032,
            "title": "Choose and Use: Users' Selection of Information Sources for Decision Support",
            "subtitle": null,
            "abstract": "Intelligent systems that record, analyze, and respond to events have become major parts of our lives. They are available as Decision Support (DS) for many tasks and can enhance the information on which decision-makers can base their decisions. Decision makers need to evaluate the available information, and they also have to decide whether to seek information from additional information sources. The information is often costly, and its costs and benefits must be weighted. Also, integrating information from multiple sources can complicate the decision task. Here, we study the combined decision process that chooses information sources and integrates them, if chosen, in a classification decision.\nIn an online experiment with 75 engineering students, we manipulated the redundancy level of information received from DS with already existing information. Participants' task in two between-subjects conditions was to classify binary events with the option to access up to two DS systems. In one of the conditions, the two DSs provided non-redundant information, and in the second condition, one of them provided fully redundant information, and the other provided non-redundant information. We found that the decision to access information was not affected by whether some information was redundant (strongly correlated with already available information). \nParticipants used the information to improve classification performance, and the improvement was significantly higher when they used non-redundant information. However, the benefits gained were smaller than predicted from a normative model. Moreover, the use of information from multiple non-correlated sources can increase mental workload, as was evident in our results, possibly because of conflicting information from different sources.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Other; Decision making; Human Factors; Human-computer interaction; Statistics; Survey"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/69d871mz",
            "frozenauthors": [
                {
                    "first_name": "Yoav",
                    "middle_name": "",
                    "last_name": "Ben Yaakov",
                    "name_suffix": "",
                    "institution": "Tel Aviv University",
                    "department": ""
                },
                {
                    "first_name": "Joachim",
                    "middle_name": "",
                    "last_name": "Meyer",
                    "name_suffix": "",
                    "institution": "Tel Aviv University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24032/galley/13626/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24032/galley/21005/download/"
                }
            ]
        },
        {
            "pk": 24036,
            "title": "Circular but Suggestive: Pragmatic Insights from Reductive Tautologies",
            "subtitle": null,
            "abstract": "What makes an explanation seem insightful? Prior work shows that even circular explanations can seem insightful when they include information from a lower level of explanation (reductive information). Here, we suggest that this impression of insight is not an illusion. Rather, circular explanations with reductive information are pragmatically instructive: they suggest at which level of description the phenomenon should be explained. In Study 1, even single-sentence circular explanations appeared insightful when infused with reductive information. In Study 2, rating circular explanations with reductive information as insightful correlated with rating them as helpful both with searching for explanatory information and with narrowing down which mechanisms an explanation should address. Study 2 also provides preliminary evidence that these ratings were not driven by prior knowledge of these circular explanations' explicit propositional content.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Learning; Reasoning; Survey"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/91t8w8t2",
            "frozenauthors": [
                {
                    "first_name": "Martin",
                    "middle_name": "",
                    "last_name": "Meyer",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Frank",
                    "middle_name": "",
                    "last_name": "Keil",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24036/galley/13630/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24036/galley/21006/download/"
                }
            ]
        },
        {
            "pk": 21689,
            "title": "Cobweb: An Incremental and Hierarchical Model of Human-Like Category Learning",
            "subtitle": null,
            "abstract": "Cobweb, a human-like category learning system, differs from most cognitive science models in incrementally constructing hierarchically organized tree-like structures guided by the category utility measure. Prior studies have shown that Cobweb can capture psychological effects such as basic-level, typicality, and fan effects. However, a broader evaluation of Cobweb as a model of human categorization remains lacking. The current study addresses this gap. It establishes Cobweb's alignment with classical human category learning effects. It also explores Cobweb's flexibility to exhibit both exemplar- and prototype-like learning within a single framework. These findings set the stage for further research on Cobweb as a robust model of human category learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Psychology; Concepts and categories; Computational Modeling; Symbolic computational modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8m85q50c",
            "frozenauthors": [
                {
                    "first_name": "Xin",
                    "middle_name": "",
                    "last_name": "Lian",
                    "name_suffix": "",
                    "institution": "Georgia Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Sashank",
                    "middle_name": "",
                    "last_name": "Varma",
                    "name_suffix": "",
                    "institution": "Georgia Tech",
                    "department": ""
                },
                {
                    "first_name": "Christopher",
                    "middle_name": "",
                    "last_name": "MacLellan",
                    "name_suffix": "",
                    "institution": "Georgia Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21689/galley/11288/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21689/galley/22082/download/"
                }
            ]
        },
        {
            "pk": 21320,
            "title": "COGGRAPH: Building bridges between cognitive science and computer graphics",
            "subtitle": null,
            "abstract": "In recent years, the field of computer graphics has achieved its longstanding dream of photorealism: modern graphics algorithms produce images that are indistinguishable from reality. Much like art at the advent of photography, then, computer graphics is now turning its gaze to the beholder: researchers are increasingly looking to cognitive science to engineer new modes of visual expression. Recent work has sought to apply insights from cognitive science to a variety of traditional graphics topics: from taking a perceptual approach to perspective, to studying the theory of mind behind animation, to applying theories of abstraction learning to build tools for geometry processing. At the same time, a wave of recent work in cognitive science has addressed fundamental questions about visual expression: for example, how humans understand and create sketches, shapes, and symbols. The field has also benefited greatly from tools and methods from computer graphics: differentiable rendering, physics simulation, and game engines have become indispensable in modeling human perception and intuitive physics. Recognizing this growing interdisciplinary exchange of ideas, we are proposing a workshop to begin building formal bridges between the cognitive science and computer graphics communities.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Art and Cognition; Creativity; Human-computer interaction; Perception; Computational Modeling"
                }
            ],
            "section": "Workshops",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/10x2163k",
            "frozenauthors": [
                {
                    "first_name": "Kartik",
                    "middle_name": "",
                    "last_name": "Chandra",
                    "name_suffix": "",
                    "institution": "MIT",
                    "department": ""
                },
                {
                    "first_name": "Anne",
                    "middle_name": "H K",
                    "last_name": "Harrington",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Katherine",
                    "middle_name": "M",
                    "last_name": "Collins",
                    "name_suffix": "",
                    "institution": "MIT",
                    "department": ""
                },
                {
                    "first_name": "Christopher",
                    "middle_name": "",
                    "last_name": "Kymn",
                    "name_suffix": "",
                    "institution": "UC Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Kushin",
                    "middle_name": "",
                    "last_name": "Mukherjee",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                },
                {
                    "first_name": "Sean",
                    "middle_name": "P",
                    "last_name": "Anderson",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Arnav",
                    "middle_name": "",
                    "last_name": "Verma",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Judith",
                    "middle_name": "E.",
                    "last_name": "Fan",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21320/galley/10919/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21320/galley/15684/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21320/galley/21765/download/"
                }
            ]
        },
        {
            "pk": 24405,
            "title": "CogME: A Cognition-Inspired Multi-Dimensional Evaluation Metric for Story Understanding",
            "subtitle": null,
            "abstract": "We introduce CogME, a cognition-inspired, multi-dimensional evaluation metric for AI models focusing on story understanding. CogME is a framework grounded in human thinking strategies and story elements that involve story understanding. With a specific breakdown of the questions, this approach provides a nuanced assessment revealing not only AI models' particular strengths and weaknesses but also the characteristics of the benchmark dataset. Our case study with the DramaQA dataset demonstrates a refined analysis of the model and the benchmark dataset. It is imperative that metrics align closely with human cognitive processes by comprehending the tasks' nature. This approach provides insights beyond traditional overall scores and paves the way for more sophisticated AI development targeting higher cognitive functions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Psychology; Human Factors; Language understanding; Computer-based experiment"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8p3137gd",
            "frozenauthors": [
                {
                    "first_name": "Minjung",
                    "middle_name": "",
                    "last_name": "Shin",
                    "name_suffix": "",
                    "institution": "Seoul National University",
                    "department": ""
                },
                {
                    "first_name": "Seongho",
                    "middle_name": "",
                    "last_name": "Choi",
                    "name_suffix": "",
                    "institution": "Seoul National University",
                    "department": ""
                },
                {
                    "first_name": "Yu-Jung",
                    "middle_name": "",
                    "last_name": "Heo",
                    "name_suffix": "",
                    "institution": "KT",
                    "department": ""
                },
                {
                    "first_name": "Minsu",
                    "middle_name": "",
                    "last_name": "Lee",
                    "name_suffix": "",
                    "institution": "Seoul National University",
                    "department": ""
                },
                {
                    "first_name": "Byoung-Tak",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Seoul National University",
                    "department": ""
                },
                {
                    "first_name": "Jeh-Kwang",
                    "middle_name": "",
                    "last_name": "Ryu",
                    "name_suffix": "",
                    "institution": "Dongguk University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24405/galley/14002/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24405/galley/21009/download/"
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            ]
        },
        {
            "pk": 24544,
            "title": "CognitiveConflict_0131",
            "subtitle": null,
            "abstract": "The use of controlled processes to resolve cognitive conflict can have various effects on performance in memory tasks. There are two hypotheses in this regard. On one hand, the use of controlled processes required to resolve cognitive conflict may impair a deep stimulus encoding, and consequently its recall. Otherwise, it would favour the encoding and subsequent memory of the stimuli involved in it. The objective of the study is both to investigate conflict effects (i.e., stimulus and response level conflict) on memory performance and the role of encoding level in modulating that effect using different paradigms (e.g., the flanker, and task switching paradigm). The preliminary results show that conflict effects seem to be independent by the level of stimulus processing. Therefore, task-switching paradigm seems to nullify both stimulus and response-level conflict effects on memory performance. Otherwise, Flanker paradigm seems to be useful to highlight conflict effects on memory.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Memory; Semantics; Computer-based experiment"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8js9f41q",
            "frozenauthors": [
                {
                    "first_name": "Nicolò",
                    "middle_name": "",
                    "last_name": "Ciarrocchi",
                    "name_suffix": "",
                    "institution": "Sapienza",
                    "department": ""
                },
                {
                    "first_name": "Pierpaolo",
                    "middle_name": "",
                    "last_name": "Zivi",
                    "name_suffix": "",
                    "institution": "Sapienza University of Rome",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24544/galley/21016/download/"
                }
            ]
        },
        {
            "pk": 24709,
            "title": "Cognitive deficits and enhancements in youth from adverse conditions: An integrative assessment using Drift Diffusion Modeling in the ABCD study",
            "subtitle": null,
            "abstract": "Childhood adversity (e.g., poverty, violence exposure) has been associated with broad cognitive deficits as well as with cognitive adaptations in specific abilities. Integrating these perspectives requires a process-level understanding of how deficit and adaptation processes operate. We investigated how adversity was associated with inhibition, attention shifting, and mental rotation in the Adolescent Brain Cognitive Development (ABCD) study (N ≈ 10,500). Using Hierarchical Bayesian Drift Diffusion Modeling, we distinguished between speed of information uptake, response caution, and stimulus encoding/response execution. We further used structural equation modeling to isolate task-general and task-specific variances in each of these processing stages. Youth with more exposure to household threat showed slower task-general processing speed, but showed intact task-specific abilities. In addition, youth with more exposure to household threat and material deprivation tended to respond more cautiously in general. These findings suggests that traditional assessments might overestimate the extent to which childhood adversity reduces specific abilities.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Evolution; Computational Modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6gn749r8",
            "frozenauthors": [
                {
                    "first_name": "Stefan",
                    "middle_name": "",
                    "last_name": "Vermeent",
                    "name_suffix": "",
                    "institution": "Utrecht University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24709/galley/21010/download/"
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24709/galley/14307/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24709/galley/18152/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24709/galley/21010/download/"
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            ]
        },
        {
            "pk": 24250,
            "title": "Cognitive Dimension Reduction: An Information-Theoretic Approach",
            "subtitle": null,
            "abstract": "We introduce a dimension reduction framework (CDR) that sheds light on how individuals simplify the multidimensional world to guide decision-making and comprehension. Our proposal posits that cognitive limitations prompt the adoption of simplified models, reducing the environment to a subset of dimensions. Within these limitations, we propose that individuals exploit both environment structure and goal relevance. Employing information theory, we formalize these principles and develop a model that explains how environmental and cognitive factors influence dimension reduction. Furthermore, we present an experimental method for the model's assessment and initial findings that support it.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Concepts and categories; Decision making; Mathematical modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8pb848ff",
            "frozenauthors": [
                {
                    "first_name": "Maya",
                    "middle_name": "",
                    "last_name": "Leshkowitz",
                    "name_suffix": "",
                    "institution": "The Hebrew University of Jerusalem",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24250/galley/13846/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24250/galley/21011/download/"
                }
            ]
        },
        {
            "pk": 21346,
            "title": "Cognitive diversity in context: US-China differences in children's reasoning, visual attention, and social cognition",
            "subtitle": null,
            "abstract": "Outward differences between cultures are very salient, with Western and East Asian cultures as a prominent comparison pair. A large literature describes cross-cultural variation in cognition, but relatively less research has explored the developmental origins of this variation. This study helps to fill the empirical gap by replicating four prominent findings documenting cross-cultural differences in children's reasoning, visual attention, and social cognition in a cross-sectional sample of 240 3-12-year-olds from the US and China. We observe cross-cultural differences in three of the four tasks and describe the distinct developmental trajectory that each task follows throughout early and middle childhood.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Attention; Causal reasoning; Cognitive development; Social cognition; Cross-cultural analysis"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4v11x3bz",
            "frozenauthors": [
                {
                    "first_name": "Alexandra",
                    "middle_name": "",
                    "last_name": "Carstensen",
                    "name_suffix": "",
                    "institution": "Arizona State University",
                    "department": ""
                },
                {
                    "first_name": "Anjie",
                    "middle_name": "",
                    "last_name": "Cao",
                    "name_suffix": "",
                    "institution": "Stanford",
                    "department": ""
                },
                {
                    "first_name": "Alvin",
                    "middle_name": "Wei Ming",
                    "last_name": "Tan",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Di",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "Johns Hopkins University",
                    "department": ""
                },
                {
                    "first_name": "Yichun",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "Fudan University",
                    "department": ""
                },
                {
                    "first_name": "Minh",
                    "middle_name": "Khong",
                    "last_name": "Bui",
                    "name_suffix": "",
                    "institution": "California State University, Fullerton",
                    "department": ""
                },
                {
                    "first_name": "Jiayi",
                    "middle_name": "",
                    "last_name": "Wang-Zhao",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Ai Nghi",
                    "middle_name": "",
                    "last_name": "Diep",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Qi",
                    "middle_name": "",
                    "last_name": "Han",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "C.",
                    "last_name": "Frank",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Caren",
                    "middle_name": "M.",
                    "last_name": "Walker",
                    "name_suffix": "",
                    "institution": "University of California San Diego",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21346/galley/10945/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21346/galley/21791/download/"
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            ]
        },
        {
            "pk": 21504,
            "title": "Cognitive Factors in Word Sense Decline",
            "subtitle": null,
            "abstract": "Word senses rise and fall due to a variety of causes. Previous research has explored how words grow novel senses, but the opposite problem of word sense decline is much less studied. Inspired by recent work on word decline, we investigate the cognitive factors that might explain the historical decline of word senses. We formalize a set of eight psycholinguistic predictors and assess their roles in discriminating declining senses from stable ones over the past two centuries in English. We find that semantic density, change in usage frequency in the semantic neighbourhood, and contextual diversity all predict word sense decline. Our study elucidates the cognitive underpinnings of word sense decline as the lexicon evolves.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Linguistics; Semantics; Computational Modeling; Corpus studies"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0142p2fx",
            "frozenauthors": [
                {
                    "first_name": "Aniket",
                    "middle_name": "",
                    "last_name": "Kali",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Yang",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Suzanne",
                    "middle_name": "",
                    "last_name": "Stevenson",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21504/galley/11103/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21504/galley/21949/download/"
                }
            ]
        },
        {
            "pk": 24301,
            "title": "Cognitive Load In Speed-Accuracy Tradeoff: Theoretical and Empirical Evidence Based on Resource-Rational Analyses",
            "subtitle": null,
            "abstract": "In simple judgment tasks, it is generally assumed that thinking for longer leads to more accurate judgments, providing better benefits as suggested by the speed-accuracy tradeoff framework. However, human cognitive resources are limited, and longer thinking induces cognitive costs such as subjective workload. Therefore, a total benefit should be considered under the tradeoff between thinking benefits (i.e., improving accuracy) and thinking costs (i.e., increasing cognitive load) as suggested by the resource rationality framework. We examined this issue using computer simulations and behavioral experiments. Our simulations showed that, if a thinking cost was introduced based on resource-rational approaches, there was an optimal length of time for maximizing a total benefit and the total benefit gradually decreased there. In addition, our experiments demonstrated that judgment accuracy did not always improve even if participants were provided a longer thinking time; conversely, longer thinking time was likely to increase their subjective workload. These results are consistent with resource rationality rather than speed-accuracy tradeoff. The importance of considering cognitive load is suggested to further understand human intelligence in the context of a speed-accuracy tradeoff.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Behavioral Science; Decision making; Computational Modeling; Computer-based experiment"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7bw9q77d",
            "frozenauthors": [
                {
                    "first_name": "Masaru",
                    "middle_name": "",
                    "last_name": "Shirasuna",
                    "name_suffix": "",
                    "institution": "Otemon Gakuin University",
                    "department": ""
                },
                {
                    "first_name": "Rina",
                    "middle_name": "",
                    "last_name": "Kagawa",
                    "name_suffix": "",
                    "institution": "University of Tsukuba",
                    "department": ""
                },
                {
                    "first_name": "Hidehito",
                    "middle_name": "",
                    "last_name": "Honda",
                    "name_suffix": "",
                    "institution": "Otemon Gakuin University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24301/galley/13897/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24301/galley/21012/download/"
                }
            ]
        },
        {
            "pk": 21696,
            "title": "Cognitive Models for Abacus Gesture Learning",
            "subtitle": null,
            "abstract": "In this paper, we developed three ACT-R cognitive models to simulate the learning process of abacus gestures. Abacus gestures are  mid-air gestures, each representing a number between 0 and 99. Our models learn to predict the response time of making an abacus gesture. We found the accuracy of a model's predictions depends on the structure of its declarative memory. A model with 100 chunks cannot simulate human response, whereas models using fewer chunks can, as segmenting chunks increase both the frequency and recency of information retrieval. Furthermore, our findings suggest that the mind is more likely to represent abacus gestures by dividing attention between two hands rather than memorizing and outputting all gestures directly. These insights have important implications for future research in cognitive science and human-computer interaction, particularly in developing vision and motor modules for mental states in existing cognitive architectures and designing intuitive and efficient mid-air gesture interfaces.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Action; Cognitive architectures; Cognitive development; Decision making; Human-computer interaction; Interactive behavior; Learning; Memory; Skill acquisition and learning; Theory of"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6mk359vh",
            "frozenauthors": [
                {
                    "first_name": "Lingyun",
                    "middle_name": "",
                    "last_name": "He",
                    "name_suffix": "",
                    "institution": "The Pennsylvania State University",
                    "department": ""
                },
                {
                    "first_name": "Duk Hee",
                    "middle_name": "",
                    "last_name": "Ka",
                    "name_suffix": "",
                    "institution": "The Pennsylvania State University",
                    "department": ""
                },
                {
                    "first_name": "Md",
                    "middle_name": "",
                    "last_name": "Ehtesham-Ul-Haque",
                    "name_suffix": "",
                    "institution": "Pennsylvania State University",
                    "department": ""
                },
                {
                    "first_name": "Syed Masum",
                    "middle_name": "",
                    "last_name": "Billah",
                    "name_suffix": "",
                    "institution": "Pennsylvania State University",
                    "department": ""
                },
                {
                    "first_name": "Farnaz",
                    "middle_name": "",
                    "last_name": "Tehranchi",
                    "name_suffix": "",
                    "institution": "The Pennsylvania State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21696/galley/11295/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21696/galley/22089/download/"
                }
            ]
        },
        {
            "pk": 24441,
            "title": "Cognitive Performance in Students: Focus on Lifestyle Factors, Brain Activity & Meditation Intervention",
            "subtitle": null,
            "abstract": "This study explores the impact of a single-session meditation intervention on cognitive performance and brain wave responses in university students (~19 years) with varying physical activity levels. In a fast-paced academic environment, understanding factors influencing cognitive health is crucial for overall well-being. Lifestyle components, including sports engagement, stress, sleep, loneliness, and anxiety, were examined using a quasi-experimental design. Participants underwent pre-and-post cognitive tests focusing on attention and working memory with simultaneous brain activity measurement. Experimental groups practiced guided meditation, while controls listened to meditation-benefits audio. Results indicate improved cognitive performance in students from both no-sports and sports groups post-meditation and control. Brain wave data aligned with cognitive performance, revealing a relaxed focus state post-meditation. This provides valuable data from student populations, supporting the development of interventions for a healthier learning environment and validating portable EEG devices for potential use in neurofeedback and cognitive neuroscience research.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Psychology; Attention; Memory; Electroencephalography (EEG)"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/443556sj",
            "frozenauthors": [
                {
                    "first_name": "Shriya",
                    "middle_name": "",
                    "last_name": "Parekh",
                    "name_suffix": "",
                    "institution": "FLAME University",
                    "department": ""
                },
                {
                    "first_name": "shruti",
                    "middle_name": "",
                    "last_name": "goyal",
                    "name_suffix": "",
                    "institution": "FLAME University",
                    "department": ""
                },
                {
                    "first_name": "Anuradha",
                    "middle_name": "",
                    "last_name": "Batabyal",
                    "name_suffix": "",
                    "institution": "FLAME University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24441/galley/14038/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24441/galley/21013/download/"
                }
            ]
        },
        {
            "pk": 24052,
            "title": "Cognitive reflection and Normality Identities: two new benchmarks for models of probability judgments",
            "subtitle": null,
            "abstract": "We propose two novel benchmarks for assessing models of probability judgments: the impact of Cognitive Reflection Test (CRT) on probability judgment expressions and 16 ``normality identities\" expected to sum to 1 under classical probability theory. We compared three models on these benchmarks – the Probability Plus Noise Model (PPN), the Bayesian Sampler (BS), and the Quantum Sequential Sampler (QSS) – using the largest dataset to date for probability judgments. Our results reveal that higher CRT scores are associated with fewer probabilistic fallacies and identity violations, a trend most accurately captured by the QSS, although we also identified QSS limitations. Regarding the normality identities, the QSS outperformed the PPN and the BS, which had difficulty with both the average values of the normality identities and their dependence on CRT scores. Additionally, we uncovered a unique ``1 crossing\" effect for normality identities N8 and N11, an effect PPN and BS cannot capture.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Behavioral Science; Decision making; Reasoning; Bayesian modeling; Computational Modeling; Mathematical modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2g41k2fs",
            "frozenauthors": [
                {
                    "first_name": "Jiaqi",
                    "middle_name": "",
                    "last_name": "Huang",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Jerome",
                    "middle_name": "",
                    "last_name": "Busemeyer",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Zo",
                    "middle_name": "",
                    "last_name": "Ebelt",
                    "name_suffix": "",
                    "institution": "City, University of London",
                    "department": ""
                },
                {
                    "first_name": "Emmanuel",
                    "middle_name": "",
                    "last_name": "Pothos",
                    "name_suffix": "",
                    "institution": "City, University of London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24052/galley/13646/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24052/galley/21014/download/"
                }
            ]
        },
        {
            "pk": 24229,
            "title": "Cognitive Science is (largely) Psychological Science",
            "subtitle": null,
            "abstract": "Cognitive science has historically been introduced as a multidisciplinary and, sometimes, an interdisciplinary study of the mind. Recent critical views of the field have questioned the foundational core and its multidisciplinary nature by suggesting that psychology has come to dominate cognitive science. As these are actively debated issues, we need further investigations. This study examines the degree of overlap between cognitive science and psychological science by comparing article keywords and departmental affiliations of authors extracted from flagship journals over the past decade (2012-2022). The results reveal that over 50% of published authors stem from psychology departments. The topics of study between the two remain quite similar as well. However, network analyses found fragmentation in terms of the methodological approaches and a considerable focus by the community of cognitive scientists on formal modeling. Based on the topics and socio-institutional analysis, we suggest that cognitive science is largely (cognitive) psychology. Implications for the field of cognitive science and its claims of multidisciplinarity are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Other; Big data; Comparative Analysis"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0m78k9jj",
            "frozenauthors": [
                {
                    "first_name": "Akhil",
                    "middle_name": "",
                    "last_name": "Abburu",
                    "name_suffix": "",
                    "institution": "Indian Institute of Technology Delhi",
                    "department": ""
                },
                {
                    "first_name": "Sumitava",
                    "middle_name": "",
                    "last_name": "Mukherjee",
                    "name_suffix": "",
                    "institution": "Indian Institute of Technology Delhi",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24229/galley/13825/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24229/galley/21015/download/"
                }
            ]
        },
        {
            "pk": 24408,
            "title": "CogSimulator: A Model for Simulating User Cognition & Behavior with Minimal Data for Tailored Cognitive Enhancement",
            "subtitle": null,
            "abstract": "The interplay between cognition and gaming, notably through educational games enhancing cognitive skills, has garnered significant attention in recent years. This research introduces the CogSimulator, a novel algorithm for simulating user cognition in small-group settings with minimal data, as the educational game Wordle exemplifies. The CogSimulator employs Wasserstein-1 distance and coordinates search optimization for hyperparameter tuning, enabling precise few-shot predictions in new game scenarios. Comparative experiments with the Wordle dataset illustrate that our model surpasses most conventional machine learning models in mean Wasserstein-1 distance, mean squared error, and mean accuracy, showcasing its efficacy in cognitive enhancement through tailored game design.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Education; Group Behaviour; Skill acquisition and learning; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4tp184s9",
            "frozenauthors": [
                {
                    "first_name": "Weizhen",
                    "middle_name": "",
                    "last_name": "Bian",
                    "name_suffix": "",
                    "institution": "HKUST",
                    "department": ""
                },
                {
                    "first_name": "Yubo",
                    "middle_name": "",
                    "last_name": "Zhou",
                    "name_suffix": "",
                    "institution": "HKBU",
                    "department": ""
                },
                {
                    "first_name": "Yuanhang",
                    "middle_name": "",
                    "last_name": "Luo",
                    "name_suffix": "",
                    "institution": "PolyU",
                    "department": ""
                },
                {
                    "first_name": "Ming",
                    "middle_name": "",
                    "last_name": "Mo",
                    "name_suffix": "",
                    "institution": "LSE",
                    "department": ""
                },
                {
                    "first_name": "Siyan",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "NUS",
                    "department": ""
                },
                {
                    "first_name": "Yikai",
                    "middle_name": "",
                    "last_name": "Gong",
                    "name_suffix": "",
                    "institution": "HKBU",
                    "department": ""
                },
                {
                    "first_name": "Ziyuan",
                    "middle_name": "",
                    "last_name": "Luo",
                    "name_suffix": "",
                    "institution": "HKBU",
                    "department": ""
                },
                {
                    "first_name": "Aobo",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "NUS",
                    "department": ""
                },
                {
                    "first_name": "Renjie",
                    "middle_name": "",
                    "last_name": "Wan",
                    "name_suffix": "",
                    "institution": "HKBU",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24408/galley/14005/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24408/galley/21017/download/"
                }
            ]
        },
        {
            "pk": 24704,
            "title": "Collateral benefits to others induce the representation of social interactions",
            "subtitle": null,
            "abstract": "People readily identify interactions based on resource transfer, such as giving. In the present study, we examine whether adults bind two agents in an interactive unit even if one caused the other to gain a resource indirectly — i.e., as a side effect of pursuing another outcome. Across five behavioral and EEG experiments, we found convergent signatures of social binding (change sensitivity and alpha-band suppression) when adults were presented with an action resulting in the collateral gain of a resource for a passive agent. No binding was observed when the action caused the collateral loss of the agent's pre-existing possession, revealing an asymmetry in how gains and losses are perceived to affect agents. Together, these findings suggest that adults interpret actions resulting in the provision of material gains as interactive, even when these are indirectly brought about.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Action; Interactive behavior; Social cognition; Electroencephalography (EEG)"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1pt0x3fh",
            "frozenauthors": [
                {
                    "first_name": "Jun",
                    "middle_name": "",
                    "last_name": "Yin",
                    "name_suffix": "",
                    "institution": "Ningbo University",
                    "department": ""
                },
                {
                    "first_name": "Qingqing",
                    "middle_name": "",
                    "last_name": "Ye",
                    "name_suffix": "",
                    "institution": "Ningbo University",
                    "department": ""
                },
                {
                    "first_name": "Denis",
                    "middle_name": "",
                    "last_name": "Tatone",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24704/galley/21018/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24704/galley/14302/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24704/galley/18143/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24704/galley/21018/download/"
                }
            ]
        },
        {
            "pk": 21535,
            "title": "Combining individuating and context-general cues in lie detection",
            "subtitle": null,
            "abstract": "To date, no account of lie-truth judgement formation has been capable of explaining how core cognitive mechanisms such as memory encoding and retrieval are employed to reach a judgement of either truth or lie. One account, the Adaptive Lie Detector theory (ALIED: Street, Bischof, Vadillo, & Kingstone, 2016) is sufficiently well defined that its assumptions may be implemented in a computational model. In this paper we describe our attempt to ground ALIED in the representations and mechanisms of the ACT-R cognitive architecture and then test the model by comparing it to human data from an experiment conducted by Street et al. (2016). The model provides a close fit to the human data and a plausible mechanistic account of how specific and general information are integrated in the formation of truth-lie judgements.",
            "language": null,
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Learning; Memory; Computational Modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0984x748",
            "frozenauthors": [
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Peebles",
                    "name_suffix": "",
                    "institution": "University of Huddersfield",
                    "department": ""
                },
                {
                    "first_name": "Chris",
                    "middle_name": "",
                    "last_name": "Street",
                    "name_suffix": "",
                    "institution": "Keele University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21535/galley/11134/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21535/galley/14611/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21535/galley/21019/download/"
                }
            ]
        },
        {
            "pk": 24731,
            "title": "Common sense reasoning about credibility",
            "subtitle": null,
            "abstract": "We often rely on others' testimony when learning about new topics, such as health benefits of a novel food. However, the sources are not always knowledgeable, helpful, or unbiased, necessitating an assessment of their credibility. Here, we present a Bayesian model of source credibility, where a listener simultaneously infers the expertise and intention of the source while trying to discern the truth. A key prediction is that rational inference of credibility requires anchoring it on some kernel of shared knowledge. We consider a scenario where both parties have noisy access to the ground truth of familiar topics (e.g., is broccoli healthy?), which serves as a basis for reasoning about a source's credibility on novel topics (e.g., is avocado healthy?). This approach provides a computational framework for understanding how people respond to information in domains like science communication and media consumption.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Philosophy; Reasoning; Social cognition; Theory of Mind; Bayesian modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0z60f8dv",
            "frozenauthors": [
                {
                    "first_name": "Peiyao",
                    "middle_name": "",
                    "last_name": "Hu",
                    "name_suffix": "",
                    "institution": "Stevens Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Mark",
                    "middle_name": "K",
                    "last_name": "Ho",
                    "name_suffix": "",
                    "institution": "Stevens Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24731/galley/21020/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24731/galley/14329/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24731/galley/18187/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24731/galley/21020/download/"
                }
            ]
        },
        {
            "pk": 24640,
            "title": "Communication and learning pressures result in clustered lexicons",
            "subtitle": null,
            "abstract": "Cross-linguistically, lexicons tend to be more phonetically clustered than required by their phonotactics; that is, words are less distinct than they could be. We use an agent-based exemplar model to investigate how this property arises over generations of language transmission under different functional pressures from learning and communication. We find that, in isolation, learnability pressures rapidly give rise to maximally clustered lexicons. When communicative pressures are also at play, clustering increases in line with a producer-side pressure to maximise similarity between words, but the rate of change is modulated by a listener-side preference for dispersion of word forms: a speaker who is trying to be understood considers what the listener is likely to understand before choosing a word to send. Overall, this work sheds light on how organisational properties of the lexicon may arise as a result of an ongoing trade-off between pressures from language learning, production and comprehension.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Evolution; Language Production; Phonology; Computational Modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/151846xb",
            "frozenauthors": [
                {
                    "first_name": "Aislinn",
                    "middle_name": "",
                    "last_name": "Keogh",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Jennifer",
                    "middle_name": "",
                    "last_name": "Culbertson",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Simon",
                    "middle_name": "",
                    "last_name": "Kirby",
                    "name_suffix": "",
                    "institution": "The University of Edinburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24640/galley/21021/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24640/galley/14237/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24640/galley/18021/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24640/galley/21021/download/"
                }
            ]
        },
        {
            "pk": 21618,
            "title": "Communication-based belief attribution: Do infants encode better others' beliefs induced via communication or the ones induced via visual cues?",
            "subtitle": null,
            "abstract": "Studies suggest that infants track others' beliefs based on visual information (Scott & Baillargeon, 2017 but see Dörrenberg, Rakoczy, Liszkowski, 2018). However, research targeting whether infants understand that others' beliefs can be induced via communication is scarce, although most of the human belief-repertoire is acquired via communication. We presented eighteen-month-olds (Experiment1:N=34; Experiment2-replication:N=35) with a false belief (FB) scenario where the initial belief was induced via communication, aiming to measure their informative pointing (for an agent mistaken about a toy's location compared to a true belief scenario). Instead of more pointing to the toy's current location, in the FB condition we found an unexpected ‚Äòaltercentric' effect: infants pointed more to the empty location where the agent falsely believed the object to be). Next, we asked whether infants show different altercentric effects for visually induced beliefs (Experiment3: N=35). Results replicated the altercentric effect, suggesting a potentially stronger encoding of visually induced beliefs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Social cognition; Theory of Mind; Gesture analysis"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7mn8x1ft",
            "frozenauthors": [
                {
                    "first_name": "Bartug",
                    "middle_name": "",
                    "last_name": "Celik",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                },
                {
                    "first_name": "Agnes",
                    "middle_name": "",
                    "last_name": "Kovacs",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21618/galley/11217/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21618/galley/14526/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21618/galley/22015/download/"
                }
            ]
        },
        {
            "pk": 24103,
            "title": "Communicative factors in the emergence of phonological dispersion",
            "subtitle": null,
            "abstract": "We investigated the emergence of dispersion in phonological systems using an established experimental paradigm in which pairs of participants play a non-linguistic communication game, taking turns to select discrete colors from a continuous underlying space and send them to each other to communicate animal silhouettes.  Over time participants established sets of signals made up of combinatorial color units, analogous to the phonemes of natural language. This allowed us to investigate the role of interactive pressures on the emergence of organizational structure in phonological inventories, principally dispersion. We manipulated minimum signal length (as a means of investigating the role of coarticulation) and the presence of probabilistic noise. We also manipulated the nature of the underlying color space. There was an effect of colorspace but not of noise or minimum signal-length. However, dispersion occurred at above-chance levels in all conditions. Our results provide evidence for the role of communicative interaction in the emergence and cultural evolution of phonological structure.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language Production; Perception; Phonology"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7332b5w1",
            "frozenauthors": [
                {
                    "first_name": "Gareth",
                    "middle_name": "",
                    "last_name": "Roberts",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                },
                {
                    "first_name": "Jianjing",
                    "middle_name": "",
                    "last_name": "Kuang",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                },
                {
                    "first_name": "Robin",
                    "middle_name": "",
                    "last_name": "Clark",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24103/galley/13697/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24103/galley/21022/download/"
                }
            ]
        },
        {
            "pk": 24526,
            "title": "Comparative study of abstract representations in humans and non-human primates",
            "subtitle": null,
            "abstract": "The ability to manipulate and recognize abstract representations seems to be a fundamental aspect of human nature, existing since the dawn of our species and transcending cultural barriers. In contrast, non-human primates exhibit very limited proficiency in recognizing abstract representations. This research delves into this human singularity for visual abstraction, through neuroimaging experiments conducted in both humans and non-human primates. Stimuli presenting the same concept (e.g. a house or a face) but varying in abstraction levels (photos, drawings, symbols, and words) were initially presented to a monkey, while intracranial recording of his brain were obtained (16 Utah arrays distributed in V1, V4 and IT). Preliminary results indicate that monkey display early signs of abstraction, particularly for evolutionarily ancient categories such as faces. MEG and fMRI recordings of human subjects are also currently underway, striving to unveil the neuronal mechanisms that set our species apart in the domain of visual abstraction.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Neuroscience; Vision; Comparative Studies; fMRI; MEG; Single-cell recording"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7d31c08h",
            "frozenauthors": [
                {
                    "first_name": "Théo",
                    "middle_name": "",
                    "last_name": "Morfoisse",
                    "name_suffix": "",
                    "institution": "Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris Saclay, NeuroSpin Center France.",
                    "department": ""
                },
                {
                    "first_name": "Maxence",
                    "middle_name": "",
                    "last_name": "Pajot",
                    "name_suffix": "",
                    "institution": "Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris Saclay, NeuroSpin Center France.",
                    "department": ""
                },
                {
                    "first_name": "Paolo",
                    "middle_name": "",
                    "last_name": "Papale",
                    "name_suffix": "",
                    "institution": "Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW)",
                    "department": ""
                },
                {
                    "first_name": "Pieter",
                    "middle_name": "",
                    "last_name": "Roelfsema",
                    "name_suffix": "",
                    "institution": "Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW)",
                    "department": ""
                },
                {
                    "first_name": "Minye",
                    "middle_name": "",
                    "last_name": "Zhan",
                    "name_suffix": "",
                    "institution": "Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris Saclay, NeuroSpin Center France.",
                    "department": ""
                },
                {
                    "first_name": "Stanislas",
                    "middle_name": "",
                    "last_name": "Dehaene",
                    "name_suffix": "",
                    "institution": "NeuroSpin Center, CEA DRF/I2BM, INSERM, Unicersité Paris-Sud, Université Paris-Saclay",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
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                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24526/galley/21023/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24526/galley/14123/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24526/galley/21023/download/"
                }
            ]
        },
        {
            "pk": 21348,
            "title": "Comparing Abstraction in Humans and Machines Using Multimodal Serial Reproduction",
            "subtitle": null,
            "abstract": "Humans extract useful abstractions of the world from noisy sensory data. Serial reproduction allows us to study how people construe the world through a paradigm similar to the game of telephone, where one person observes a stimulus and reproduces it for the next to form a chain of reproductions. Past serial reproduction experiments typically employ a single sensory modality, but humans often communicate abstractions of the world to each other through language. To investigate the effect language on the formation of abstractions, we implement a novel multimodal serial reproduction framework by asking people who receive a visual stimulus to reproduce it in a linguistic format, and vice versa. We ran unimodal and multimodal chains with both humans and GPT-4 and find that adding language as a modality has a larger effect on human reproductions than GPT-4's. This suggests human visual and linguistic representations are more dissociable than those of GPT-4.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Psychology; Language and thought; Bayesian modeling; Large Language Models"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0k26s3b7",
            "frozenauthors": [
                {
                    "first_name": "Sreejan",
                    "middle_name": "",
                    "last_name": "Kumar",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Raja",
                    "middle_name": "",
                    "last_name": "Marjieh",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Byron",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Declan",
                    "middle_name": "",
                    "last_name": "Campbell",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "MICHAEL",
                    "middle_name": "Y",
                    "last_name": "HU",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Umang",
                    "middle_name": "",
                    "last_name": "Bhatt",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Brenden",
                    "middle_name": "",
                    "last_name": "Lake",
                    "name_suffix": "",
                    "institution": "NYU",
                    "department": ""
                },
                {
                    "first_name": "Tom",
                    "middle_name": "",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21348/galley/10947/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21348/galley/21793/download/"
                }
            ]
        },
        {
            "pk": 21705,
            "title": "Comparing online and post-processing pronunciation correction during orthographic incidental learning: A computational study with the BRAID-Acq model",
            "subtitle": null,
            "abstract": "Reading acquisition primarily relies on orthographic learning.\nBehavioral studies show that familiarity with a novel word's\npronunciation facilitates learning, particularly in semantically\nmeaningful contexts. Two main components of orthographic\nlearning are commonly described: perceptual processing of\nthe visual stimulus, to infer corresponding phonological rep-\nresentations, and “pronunciation correction”, to correct errors\nfrom perceptual processing. Currently, pronunciation correc-\ntion has not been featured in reading acquisition computa-\ntional models. This study uses BRAID-Acq, a reading ac-\nquisition model, to implement and compare two pronunciation\ncorrection mechanisms (an “online” and a “post-processing”\nvariant). We simulated learning of words with and without\nprior phonological knowledge and explored the impact of con-\ntext strength and size on learning. Results indicate that both\nmechanisms improve decoding. However, the post-processing\nmechanism induced implausible lexicalization for words with-\nout prior phonological knowledge, while the online mecha-\nnism did not. Overall, our simulation results suggest that pro-\nnunciation correction could be construed as an online process.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Language learning; Reading; Bayesian modeling; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3sz9k56p",
            "frozenauthors": [
                {
                    "first_name": "Alexandra",
                    "middle_name": "",
                    "last_name": "Steinhilber",
                    "name_suffix": "",
                    "institution": "Laboratoire de Psychologie et NeuroCognition",
                    "department": ""
                },
                {
                    "first_name": "Sylviane",
                    "middle_name": "",
                    "last_name": "Valdois",
                    "name_suffix": "",
                    "institution": "CNRS et Université Grenoble Alpes",
                    "department": ""
                },
                {
                    "first_name": "Julien",
                    "middle_name": "",
                    "last_name": "Diard",
                    "name_suffix": "",
                    "institution": "CNRS - Université Grenoble Alpes",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21705/galley/11304/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21705/galley/22098/download/"
                }
            ]
        },
        {
            "pk": 24710,
            "title": "Comparing the effect of single outliers and outlier clusters on trend estimation in scatterplots",
            "subtitle": null,
            "abstract": "Scatterplots are commonly used data visualizations to depict relationships between variables. There are inconsistent findings in the literature regarding how outliers in scatterplots affect trendline estimates. Correll & Heer (2017) found no difference for trendline estimations between the no-outlier and the outlier conditions consisting of a separate group of items creating an outlier cluster. However, Ciccione et al. (2022) showed that single outlier points might be included in trendline estimations. To investigate whether an outlier cluster was perceived as a salient and separate unit and thus excluded from the remaining data points, we directly compared the effects of single and multiple outliers on trendline estimations, controlling for correlation strength, outlier position and trend direction. Participants drew trendlines. We found that participants included single outliers more than they've included outlier clusters into the trendlines; this pattern was similar across all other control variables; suggesting grouping might play a role in this process.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Pattern recognition; Vision; Computer-based experiment"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0km5d4kq",
            "frozenauthors": [
                {
                    "first_name": "Özgür",
                    "middle_name": "",
                    "last_name": "Saydır",
                    "name_suffix": "",
                    "institution": "Koc University",
                    "department": ""
                },
                {
                    "first_name": "Aysecan",
                    "middle_name": "",
                    "last_name": "Boduroglu",
                    "name_suffix": "",
                    "institution": "Koc University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24710/galley/21024/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24710/galley/14308/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24710/galley/18154/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24710/galley/21024/download/"
                }
            ]
        },
        {
            "pk": 24155,
            "title": "Comparing Theories that Posit a Role for Task Features in Strategy Selection",
            "subtitle": null,
            "abstract": "Salient features of a task play an important role in how people create task representations which then influence strategy selection for accomplishing the task. We examined two theories, Represent-Construct-Choose-Learn (RCCL) and Rational Metareasoning (RM), both of which incorporate task features into their models of strategy selection. RCCL theory posits that when a strategy's success rate is low, it indicates that the task representation is not useful and those represented features are irrelevant in this case so people tend to drop these features from the task representation. Conversely, RM theory posits that strategy selection is based on consideration of all available features, with no discrete changes in the features incorporated into the task representation. A study was conducted to examine how participants changed their strategy choices based on the success rate of using a specific task feature. The results showed that neither theory aligned closely with empirical data.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Learning; Problem Solving"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6zg5711c",
            "frozenauthors": [
                {
                    "first_name": "Xinyu",
                    "middle_name": "",
                    "last_name": "Xie",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                },
                {
                    "first_name": "Jarrod",
                    "middle_name": "",
                    "last_name": "Moss",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24155/galley/13751/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24155/galley/21026/download/"
                }
            ]
        },
        {
            "pk": 24016,
            "title": "Comparing the Threshold and Prototype Model for Gradable Adjectives",
            "subtitle": null,
            "abstract": "In logical theories of meaning, threshold and prototype models are two distinctive formal approaches. In cognitive science literature, however, where the two models are operationalized, there is support for the use of a threshold model in categorization (Schmidt, Goodman, Barner, & Tenenbaum, 2009; Ramotowska, Haaf, Van Maanen, & Szymanik, 2022) as well as sup- port for the prototype model (Douven, 2016; Douven, Wenmackers, Jraissati, & Decock, 2017), and in many cases the two models are used interchangeably (Kruschke, 2008). We test for the case of relative gradable adjectives whether a) there is a difference between predicted degrees of membership from the two models when relying on explicit reports of threshold and prototype values, and b) which of the models better pre- dicts behavioral data from categorization tasks. Results suggest that prototype and threshold models are highly predictive of behaviour in a categorization task and that the two models yield similar results with a slight advantage of the threshold model.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Language and thought; Representation; Comparative Analysis; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9w855420",
            "frozenauthors": [
                {
                    "first_name": "Tamar",
                    "middle_name": "",
                    "last_name": "Johnson",
                    "name_suffix": "",
                    "institution": "University of Amsterdam",
                    "department": ""
                },
                {
                    "first_name": "Alexandra",
                    "middle_name": "",
                    "last_name": "Sarafoglou",
                    "name_suffix": "",
                    "institution": "University of Amsterdam",
                    "department": ""
                },
                {
                    "first_name": "Julia",
                    "middle_name": "M",
                    "last_name": "Haaf",
                    "name_suffix": "",
                    "institution": "University of Potsdam",
                    "department": ""
                },
                {
                    "first_name": "Ingmar",
                    "middle_name": "",
                    "last_name": "Visser",
                    "name_suffix": "",
                    "institution": "University of Amsterdam",
                    "department": ""
                },
                {
                    "first_name": "Jakub",
                    "middle_name": "",
                    "last_name": "Szymanik",
                    "name_suffix": "",
                    "institution": "University of Trento",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24016/galley/13610/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24016/galley/21025/download/"
                }
            ]
        },
        {
            "pk": 21571,
            "title": "Complexity-Theoretic Limits on the Promises of Artificial Neural Network Reverse-Engineering",
            "subtitle": null,
            "abstract": "Emerging folklore in the cognitive sciences suggests that interpretability techniques to reverse-engineer artificial neural networks (ANNs) could speed up discovery and theory-building. For many researchers in psychology, linguistics, neuroscience, and artificial intelligence (AI), the full observability and perturbability of ANNs trained on complex tasks affords a shortcut to domain insights, cognitive theories, neurocognitive models, application improvement, and user safety. Folklore intuitions, however, are typically disconnected from other relevant knowledge. Here we examine these intuitions formally by drawing relevant connections to computational complexity theory. We model interpretability queries computationally and analyze their resource demands for biological/artificial high-level cognition. We prove mathematically that, contrary to folklore, basic circuit-finding queries in classic ANNs are already infeasibly demanding to answer even approximately. We discuss how interdisciplinary integration can mitigate this disconnect and situate the broader implications for the cognitive sciences, the philosophy of AI-fueled discovery, and AI ethics.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Cognitive Neuroscience; Computer Science; Philosophy; Psychology; Computational Modeling; Mathematical modeling; Neural Networks"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2h78n1hj",
            "frozenauthors": [
                {
                    "first_name": "Federico",
                    "middle_name": "",
                    "last_name": "Adolfi",
                    "name_suffix": "",
                    "institution": "Ernst-Strüngmann Institute for Neuroscience",
                    "department": ""
                },
                {
                    "first_name": "Martina",
                    "middle_name": "G.",
                    "last_name": "Vilas",
                    "name_suffix": "",
                    "institution": "Goethe University Frankfurt",
                    "department": ""
                },
                {
                    "first_name": "Todd",
                    "middle_name": "",
                    "last_name": "Wareham",
                    "name_suffix": "",
                    "institution": "Memorial University of Newfoundland",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21571/galley/11170/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21571/galley/21964/download/"
                }
            ]
        },
        {
            "pk": 21385,
            "title": "Compositional Generalization in Distributional Models of Semantics: Transformer-based Language Models are Architecturally Advantaged",
            "subtitle": null,
            "abstract": "An important aspect of language comprehension is learning and generalizing complex lexical relations. For instance, having learned that the phrase preserve cucumbers predicts vinegar and that preserve berries predicts dehydrator, one should be able to infer that the novel phrase preserve peppers is more compatible with vinegar, because pepper is more similar to cucumber. We studied the ability to perform such (compositional) generalization in distributional models trained on an artificial corpus with strict semantic regularities. We found that word-encoding models failed to learn the multi-way lexical dependencies. Recurrent neural networks learned those dependencies but struggled to generalize to novel combinations. Only mini GPT-2, a minified version of the Transformer GPT-2, succeeded in both learning and generalization. Because successful generalization in our tasks requires capturing the relationship between a phrase and a word, we argue that mini GPT-2 acquired hierarchical representations that approximate phrase structure. Our results show that, compared to older models, Transformers are architecturally advantaged to perform compositional generalization.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Language understanding; Representation; Semantic memory; Knowledge representation; Neural Networks"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5h55z27v",
            "frozenauthors": [
                {
                    "first_name": "Shufan",
                    "middle_name": "",
                    "last_name": "Mao",
                    "name_suffix": "",
                    "institution": "University of Illinois at Urbana Champaign",
                    "department": ""
                },
                {
                    "first_name": "Philip",
                    "middle_name": "A",
                    "last_name": "Huebner",
                    "name_suffix": "",
                    "institution": "Pattern",
                    "department": ""
                },
                {
                    "first_name": "Jon",
                    "middle_name": "",
                    "last_name": "Willits",
                    "name_suffix": "",
                    "institution": "University of Illinois at Urbana-Champaign",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21385/galley/10984/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21385/galley/21830/download/"
                }
            ]
        },
        {
            "pk": 24219,
            "title": "Compositionality in Chinese Characters: Evidence from English-speaking Children",
            "subtitle": null,
            "abstract": "Compositionality is a core property of language: the meaning of sentences is derived from the meanings of individual words and rules for combining their meanings (Partee, 1984). Human adults have been shown to make compositional generalizations across many domains such as language, visual concept learning, and sequence learning. Few studies have investigated conceptual compositionality in young children. In two experiments with English-speaking 5- to 8-year-old children who have not been exposed to Chinese characters, we found that after a brief training session, they were able to generalize the newly learned radical-meaning pairs to new characters compositionally. Our results suggest that by age 5, children can make meaningfully compositional generalizations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Learning"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/29n2g4r2",
            "frozenauthors": [
                {
                    "first_name": "Min",
                    "middle_name": "",
                    "last_name": "Tang",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Rongzhi",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                },
                {
                    "first_name": "Fei",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "UC Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24219/galley/13815/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24219/galley/21029/download/"
                }
            ]
        },
        {
            "pk": 21317,
            "title": "Compositionality in minds, brains and machines: a unifying goal that cuts across cognitive sciences",
            "subtitle": null,
            "abstract": "Compositionality, or the ability to build complex representations from discrete elements, is an essential ingredient of human intelligence. Compositionality enables people to think productively, learn fast from limited experience, and generalize knowledge to new contexts without re-learning from scratch. It is also essential in information processing systems to efficiently represent structured data and has seen application in compression and symbolic Artificial Intelligence (AI). Historically, the notion of compositionality played a central role in linguistic theory and philosophy of mind. More recently, it is attracting a surge of interest throughout the domains of cognitive science. Compositional processes are leveraged for elucidating the nature of mental representations in cognition (Dehaene et al., 2022), understanding the functional organisation of the brain (Agrawal et al., 2019), or building Artificial Intelligence systems that are robust to changes in the environment (Hupkes et al., 2020).",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Cognitive Neuroscience; Linguistics; Neuroscience; Psychology"
                }
            ],
            "section": "Workshops",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6105t998",
            "frozenauthors": [
                {
                    "first_name": "Barbara",
                    "middle_name": "",
                    "last_name": "Pomiechowska",
                    "name_suffix": "",
                    "institution": "University of Birmingham",
                    "department": ""
                },
                {
                    "first_name": "Rachel",
                    "middle_name": "",
                    "last_name": "Dudley",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                },
                {
                    "first_name": "Lionel",
                    "middle_name": "",
                    "last_name": "Wong",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Mathias",
                    "middle_name": "",
                    "last_name": "Sablé-Meyer",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
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            ],
            "date_submitted": null,
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        },
        {
            "pk": 24035,
            "title": "Compositional learning of functions in humans and machines",
            "subtitle": null,
            "abstract": "The human ability to learn and compose conceptual operations is foundational to making flexible generalizations, such as creating new dishes from known cooking processes. Beyond naive chaining of functions, there is evidence from the linguistic literature that people can learn and apply context-sensitive, interactive rules, such that output production depends on context changes induced by different function orderings. Extending the investigation into the visual domain, we developed a function learning paradigm to explore the capacity of humans and neural network models in learning and reasoning with compositional functions under varied interaction conditions. Following brief training on individual functions, human participants were assessed on composing two learned functions, in ways covering four main interaction types, including instances in which the application of the first function creates or removes the context for applying the second function. Our findings indicate that humans can make zero-shot generalizations on novel visual function compositions across interaction conditions, demonstrating sensitivity to contextual changes. A comparison with a neural network model on the same task reveals that, through the meta-learning for compositionality (MLC) approach, a standard sequence-to-sequence Transformer can approximate a strong function learner, and also mimic human error patterns with additional fine-tuning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Psychology; Learning; Reasoning; Neural Networks"
                }
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            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1kg1p6sr",
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                {
                    "first_name": "Yanli",
                    "middle_name": "",
                    "last_name": "Zhou",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Brenden",
                    "middle_name": "",
                    "last_name": "Lake",
                    "name_suffix": "",
                    "institution": "NYU",
                    "department": ""
                },
                {
                    "first_name": "Adina",
                    "middle_name": "",
                    "last_name": "Williams",
                    "name_suffix": "",
                    "institution": "Meta Platforms Inc.",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24035/galley/21028/download/"
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        {
            "pk": 24000,
            "title": "Composition as nonlinear combination in semantic space: Exploring the effect of compositionality on Chinese compound recognition",
            "subtitle": null,
            "abstract": "Most Chinese words are compounds formed through the combination of meaningful characters. Yet, due to compositional complexity, it is poorly understood how this combinatorial process affects the access to the whole-word meaning. In the present study, we turned to the recent development in compositional distributional semantics (Marelli et al., 2017), and employed a deep neural network to learn the less-than-systematic relationship between the constituent characters and the compound words. Based on the compositional representations derived from the computational model, we quantified compositionality as the degree of overlap between the compositional and the lexicalized representations as well as the degree of distinctness of the compositional representation. We observed that these two compositional attributes can affect compound recognition over and above the effects of constituent character features and compound features. Moreover, we found that this effect was increasingly stronger when holistic access to the compound meaning became more challenging. These findings therefore, from a computational perspective, provided new evidence for the combinatorial process involved in Chinese word recognition, which also shed light on the universal process of compound comprehension.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Morphology; Reading; Semantics"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/90p7t5br",
            "frozenauthors": [
                {
                    "first_name": "Tianqi",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "The University of Hong Kong",
                    "department": ""
                },
                {
                    "first_name": "Xu",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "Shanghai Jiao Tong University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24000/galley/13594/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24000/galley/21027/download/"
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        },
        {
            "pk": 24209,
            "title": "Computational characterization of the role of an attention schema in controlling visuospatial attention",
            "subtitle": null,
            "abstract": "How does the brain control attention? The Attention Schema Theory suggests that the brain explicitly models its state of attention, termed an attention schema, for its control. However, it remains unclear under which circumstances an attention schema is computationally useful, and whether it can emerge in a learning system without hard-wiring. To address these questions, we trained a reinforcement learning agent with attention to track and catch a ball in a noisy environment. Crucially, the agent had additional resources that it could freely use. We asked under which conditions these additional resources develop an attention schema to track attention. We found that the more uncertain the agent was about the location of its attentional window, the more it benefited from these additional resources, which developed an attention schema. Together, these results indicate that an attention schema emerges in simple learning systems where attention is important and difficult to track.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Attention; Intelligent agents; Agent-based Modeling; Neural Networks"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1516x0js",
            "frozenauthors": [
                {
                    "first_name": "Lotta",
                    "middle_name": "Marlen",
                    "last_name": "Piefke",
                    "name_suffix": "",
                    "institution": "University Osnabrück",
                    "department": ""
                },
                {
                    "first_name": "Adrien",
                    "middle_name": "",
                    "last_name": "Doerig",
                    "name_suffix": "",
                    "institution": "University of Osnabrück",
                    "department": ""
                },
                {
                    "first_name": "Tim",
                    "middle_name": "",
                    "last_name": "Kietzmann",
                    "name_suffix": "",
                    "institution": "University of Osnabrück",
                    "department": ""
                },
                {
                    "first_name": "Sushrut",
                    "middle_name": "",
                    "last_name": "Thorat",
                    "name_suffix": "",
                    "institution": "Osnabrück University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24209/galley/21031/download/"
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            ]
        },
        {
            "pk": 24678,
            "title": "Computational Principles of Caregiving",
            "subtitle": null,
            "abstract": "I formalize the problem of care in the mathematical language of sequential decision-making. Drawing upon insights from developmental psychology, robotics, and computational cognitive modeling, I conceptualize care as a dynamic interplay between the caregiver ('one-caring') and the care recipient ('cared-for'). Caring actions maximize the utility of the cared-for at a future point when they are required to act autonomously. Since this quantity cannot be directly optimized, the focus is on enabling increasing levels of autonomy through environmental shaping, risk reduction, and safe exploration. I distinguish caregiving from helping and teaching by care's focus on exploration and autonomy that increase capacity over time. In the context of elderly care, the emphasis shifts towards preserving rather than enhancing capacity. Finally, I consider the role of caregiving in the development of moral values and the possibility of artificially intelligent agents that might someday care for us.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Philosophy; Psychology; Cognitive development; Learning; Machine learning; Social cognition; Theory of Mind; Computational Modeling; Mathematical modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/76n200f8",
            "frozenauthors": [
                {
                    "first_name": "Max",
                    "middle_name": "",
                    "last_name": "Kleiman-Weiner",
                    "name_suffix": "",
                    "institution": "University of Washington",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24678/galley/21032/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24678/galley/14276/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24678/galley/18092/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24678/galley/21032/download/"
                }
            ]
        },
        {
            "pk": 21328,
            "title": "Computational Social Cognition: Approaches and challenges",
            "subtitle": null,
            "abstract": "Predicting the actions and reactions of others is crucial to suc- cessful social interaction. When deciding whether to bluff in a game of poker, we consider the chances that the other players will fold or continue to play and unmask our bluff. When deciding whether to tell our boss that their plans are likely to have adverse effects, we consider a range of reac- tions, from being grateful for our honesty to being dismissed out of spite. Such predictions are highly uncertain and com- plex, not least because the other's (re)actions usually result from them making equally complex and uncertain inferences about us. Nevertheless, we are often remarkably successful – although sometimes utterly wrong – in our social inferences. How do we explain these successes and failures?",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Social cognition; Theory of Mind; Computational Modeling"
                }
            ],
            "section": "Symposia",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7930b0r3",
            "frozenauthors": [
                {
                    "first_name": "Ismail",
                    "middle_name": "",
                    "last_name": "Guennouni",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Joseph M",
                    "middle_name": "",
                    "last_name": "Barnby",
                    "name_suffix": "",
                    "institution": "Royal Holloway, University of London",
                    "department": ""
                },
                {
                    "first_name": "Julian",
                    "middle_name": "",
                    "last_name": "Jara-Ettinger",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Rebecca",
                    "middle_name": "",
                    "last_name": "Saxe",
                    "name_suffix": "",
                    "institution": "MIT",
                    "department": ""
                },
                {
                    "first_name": "Maarten",
                    "middle_name": "",
                    "last_name": "Speekenbrink",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21328/galley/21773/download/"
                }
            ]
        },
        {
            "pk": 21409,
            "title": "Computational Thought Experiments for a  More Rigorous Philosophy and Science of the Mind",
            "subtitle": null,
            "abstract": "We offer philosophical motivations for a method we call Virtual World Cognitive Science (VW CogSci), in which re- searchers use virtual embodied agents that are embedded in virtual worlds to explore questions in the field of Cognitive Science. We focus on questions about mental and linguistic representation and the ways that such computational modeling can add rigor to philosophical thought experiments, as well as the terminology used in the scientific study of such representations. We find that this method forces researchers to take a god's-eye view when describing dynamical relationships be- tween entities in minds and entities in an environment in a way that eliminates the need for problematic talk of belief and concept *types*, such as *the belief that cats are silly*, and *the concept CAT*, while preserving belief and concept *tokens* in individual cognizers' minds. We conclude with some further key advantages of VW CogSci for the scientific study of mental and linguistic representation and for Cognitive Science more broadly.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Philosophy; Robotics; Cognitive development; Embodied Cognition"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8p8357rh",
            "frozenauthors": [
                {
                    "first_name": "Iris",
                    "middle_name": "",
                    "last_name": "Oved",
                    "name_suffix": "",
                    "institution": "Independent Scholar",
                    "department": ""
                },
                {
                    "first_name": "Nikhil",
                    "middle_name": "",
                    "last_name": "Krishnaswamy",
                    "name_suffix": "",
                    "institution": "Colorado State University",
                    "department": ""
                },
                {
                    "first_name": "James",
                    "middle_name": "",
                    "last_name": "Pustejovsky",
                    "name_suffix": "",
                    "institution": "Brandeis University",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "K",
                    "last_name": "Hartshorne",
                    "name_suffix": "",
                    "institution": "Boston College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21409/galley/21854/download/"
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        },
        {
            "pk": 24146,
            "title": "Concept Alignment as a Prerequisite for Value Alignment",
            "subtitle": null,
            "abstract": "Value alignment is essential for building AI systems that can safely and reliably interact with people. However, what a person values---and is even capable of valuing---depends on the concepts that they are currently using to understand and evaluate what happens in the world. The dependence of values on concepts means that concept alignment is a prerequisite for value alignment---agents need to align their representation of a situation with that of humans in order to successfully align their values. Here, we formally analyze the concept alignment problem in the inverse reinforcement learning setting, show how neglecting concept alignment can lead to systematic value mis-alignment, and describe an approach that helps minimize such failure modes by jointly reasoning about a person's concepts and values. Additionally, we report experimental results with human participants showing that humans reason about the concepts used by an agent when acting intentionally, in line with our joint reasoning model.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Computer Science; Psychology; Bayesian modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9902x9hh",
            "frozenauthors": [
                {
                    "first_name": "Sunayana",
                    "middle_name": "",
                    "last_name": "Rane",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Mark",
                    "middle_name": "K",
                    "last_name": "Ho",
                    "name_suffix": "",
                    "institution": "Stevens Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Ilia",
                    "middle_name": "",
                    "last_name": "Sucholutsky",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Tom",
                    "middle_name": "",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-02T03:00:00+09:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24146/galley/21033/download/"
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}