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The Theory of Mind Utility: A Formal Account of Mentalizing

arXiv 2606.12721 ↗First posted 10 Jun 2026cs.AIcited by 0

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Abstract (arXiv)

Inferring another person's beliefs requires reconstructing their information access history: what they encountered, in what order, from whom, and with what credibility. Existing formal accounts of theory of mind generally treat beliefs as given. We introduce the Theory of Mind Utility (ToM-U), a computational-level theory of how beliefs are formed from information-access history. ToM-U represents a person's epistemic situation as a Local Epistemic World Model (LEWM): a directed typed graph linking agents, information, and belief-like states. ToM-U generates candidate LEWMs, limits how deeply a person reasons about another's reasoning, and evaluates each candidate against observed behavior. A sufficiently coherent candidate is accepted, while a failed one leaves a structured residue that shapes later reasoning. Together, these components formalize a distinct cognitive process that operates across social reasoning. The architecture supports testable predictions about when mentalizing will fail and how those failures will affect subsequent attempts.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 59 references that are in the map. First posted on arXiv 10 Jun 2026.

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References · 4

  1. 2018World Modelscited by 1,444
  2. 2023Large Language Models Fail on Trivial Alterations to Theory-of-Mind Taskscited by 288
  3. 2023Evaluating Large Language Models in Theory of Mind Taskscited by 217
  4. 2024Spontaneous Theory of Mind for Artificial Intelligencecited by 3

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  1. 2024Language Models Represent Beliefs of Self and Others
  2. 2026Dynamic Theory of Mind as a Temporal Memory Problem: Evidence from Large Language Models
  3. 2026Avalon-ToM-Bench: Evaluating Fine-Grained Theory of Mind via Asymmetric Game Mechanics
  4. 2026Beyond Words: Evaluating and Bridging Epistemic Divergence in User-Agent Interaction via Theory of Mind
  5. 2024Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind
  6. 2026Beyond Sally-Anne: Evaluating Theory of Mind in LLMs using Epistemic Schelling Points
  7. 2023HI-TOM: A Benchmark for Evaluating Higher-Order Theory of Mind Reasoning in Large Language Models
  8. 2024SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs