most citedSimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs

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cs.CL2026★ 2 cited

SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs

Yuling Gu, Oyvind Tafjord, Hyunwoo Kim +4

Large language models (LLMs) are increasingly tested for a "Theory of Mind" (ToM) - the ability to attribute mental states to oneself and others. Yet most evaluations stop at expli…

cs.CL2024

Digital Socrates: Evaluating LLMs through Explanation Critiques

Yuling Gu, Oyvind Tafjord, Peter Clark

While LLMs can provide reasoned explanations along with their answers, the nature and quality of those explanations are still poorly understood. In response, our goal is to define…

cs.CL2024

PROC2PDDL: Open-Domain Planning Representations from Texts

Tianyi Zhang, Li Zhang, Zhaoyi Hou +5

Planning in a text-based environment continues to be a major challenge for AI systems. Recent approaches have used language models to predict a planning domain definition (e.g., PD…