{"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/"}]}