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{
    "pk": 49126,
    "title": "Building computational models of social cognition in memo",
    "subtitle": null,
    "abstract": "One of the most influential computational paradigms in modern cognitive science is the Bayesian modeling of social cognition. This paradigm models people's intuitions about other agents in terms of recursive probabilistic reasoning: agents are treated as approximately-rational decision-makers, who make Bayesian inferences about *other* agents' mental states from their observable behavior. Computational models designed in this tradition have been used in seminal work on theory-of-mind, language and communication, emotion understanding, and many other key areas of interest in cognitive science.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Workshop",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/30k5x6zk",
    "frozenauthors": [
        {
            "first_name": "Kartik",
            "middle_name": "",
            "last_name": "Chandra",
            "name_suffix": "",
            "institution": "MIT",
            "department": ""
        },
        {
            "first_name": "Sean",
            "middle_name": "Dae",
            "last_name": "Houlihan",
            "name_suffix": "",
            "institution": "Dartmouth College",
            "department": ""
        },
        {
            "first_name": "Max",
            "middle_name": "",
            "last_name": "Kleiman-Weiner",
            "name_suffix": "",
            "institution": "University of Washington",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2025-01-01T18:00:00Z",
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}