Papers by Yude Zou

1 papers
Text2World: Benchmarking Large Language Models for Symbolic World Model Generation (2025.findings-acl)

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Challenge: Recent studies have encountered limitations in leveraging large language models to generate symbolic world models.
Approach: They propose a benchmarking framework based on planning domain definition language (PDDL) that employs multi-criteria, execution-based metrics for a more robust evaluation.
Outcome: The proposed model outperforms models trained with large-scale reinforcement learning, but lacks the robustness needed to perform in world modeling.

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