arXiv Computation and Language October 22, 2026 By Nithin Sivakumaran, Ali Payani, Hyunji Lee, Mohit Bansal, Elias Stengel-Eskin

ToM2Vec: Continuous Theory-of-Mind Tokens for Multi-Agent Coordination

Read the original on arXiv Computation and Language →

ToM2Vec introduces continuous theory-of-mind tokens that enable large language model agents to reason about multiple possible partner states in multi‑agent settings. By training these tokens to abstract partner thoughts, the model generates latent representations that condition agents’ thoughts and actions, improving performance across collaborative, competitive, and mixed‑motive environments. The approach demonstrates that latent reasoning outperforms text‑based reasoning and generalizes to unseen partner models, with tokens encoding partner beliefs, desires, and next actions.

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