Mind Your Theory: Theory of Mind Goes Deeper Than Reasoning
December 18, 2024 Β· Declared Dead Β· π Annual Meeting of the Association for Computational Linguistics
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Authors
Eitan Wagner, Nitay Alon, Joseph M. Barnby, Omri Abend
arXiv ID
2412.13631
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CL
Citations
7
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
4 months ago
Abstract
Theory of Mind (ToM) capabilities in LLMs have recently become a central object of investigation. Cognitive science distinguishes between two steps required for ToM tasks: 1) determine whether to invoke ToM, which includes the appropriate Depth of Mentalizing (DoM), or level of recursion required to complete a task; and 2) applying the correct inference given the DoM. In this position paper, we first identify several lines of work in different communities in AI, including LLM benchmarking, ToM add-ons, ToM probing, and formal models for ToM. We argue that recent work in AI tends to focus exclusively on the second step which are typically framed as static logic problems. We conclude with suggestions for improved evaluation of ToM capabilities inspired by dynamic environments used in cognitive tasks.
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