Article Instance

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{
    "pk": 50301,
    "title": "Three Levels for Large Language Model Cognition",
    "subtitle": null,
    "abstract": "Marr's three-level hypothesis is widely applied to information processing systems, including large language models (LLMs). Despite its usefulness, applying it to LLMs proves it to be a leaky abstraction: demarcating between levels tends to be a choice that needs to be argued for. The paper explores the three levels separately and offers paradigm examples of explanations for each level. It closes with a pragmatist proposal for studying LLM cognition, inspired by the philosophy of cognitive neuroscience.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Artificial Intelligence; Neuroscience; Philosophy; Machine learning"
        }
    ],
    "section": "Member Abstracts with Poster Presentation",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/79f59030",
    "frozenauthors": [
        {
            "first_name": "Eleni",
            "middle_name": "",
            "last_name": "Angelou",
            "name_suffix": "",
            "institution": "CUNY",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2025-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50301/galley/38263/download/"
        }
    ]
}