Papers by Glen Berseth

    1 papers
    Enhancing Agent Learning through World Dynamics Modeling (2024.findings-emnlp)

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    Challenge: Existing methods assume that large language models have a complete understanding of their environment, overlooking potential gaps in their grasp of actual world dynamics.
    Approach: They propose a framework that discovers world dynamics from a small number of demonstrations, verifies the correctness of these dynamics, and evolves new, advanced dynamics tailored to the current situation.
    Outcome: The proposed framework discovers, verifies, and evolves world dynamics from a small number of demonstrations, and compares the automatically generated dynamics with human-annotated world dynamics.

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