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MeetingToM: Evaluating Multimodal LLMs on Theory-of-Mind Reasoning in Multi-Party Meetings

arXiv cs.CL Multimodal & Generative Ziyi Wang, Yuhang Wu, Dongxu Piao, Xingyu Liu, Tianhui Zhou, Miao Liu 2026-07-21

TL;DR - MeetingToM is a benchmark for evaluating theory-of-mind reasoning by multimodal LLMs in naturalistic multi-party meetings. It matters because current models struggle to combine verbal and nonverbal cues to infer hidden attitudes and distinguish genuine agreement from socially pressured pseudo-consensus.

  • Evaluates mental-state prediction, addressee understanding, and group consensus reasoning.
  • Targets latent social dynamics rather than only overt, externally verifiable signals.
  • Introduces pseudo-consensus as a meeting-specific challenge involving apparent agreement despite private dissent.
  • Analyses of representative models reveal persistent weaknesses in nonverbal cue integration and hidden-attitude inference.

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