# Infusing Theory of Mind into Socially Intelligent LLM Agents Source: [Infusing Theory of Mind into Socially Intelligent LLM Agents]() Collection index: [llms.txt]() Data updated: 2026-04-15T05:00:04.591Z Authors: EunJeong Hwang, Yuwei Yin, Giuseppe Carenini, Peter West, Vered Shwartz Published: 2025-09-26T20:07:34.000Z ## Abstract Theory of Mind (ToM)-an understanding of the mental states of others-is a key aspect of human social intelligence, yet, chatbots and LLM-based social agents do not typically integrate it. In this work, we demonstrate that LLMs that explicitly use ToM get better at dialogue, achieving goals more effectively. After showing that simply prompting models to generate mental states between dialogue turns already provides significant benefit, we further introduce ToMAgent (ToMA), a ToM-focused dialogue agent. ToMA is trained by pairing ToM with dialogue lookahead to produce mental states that are maximally useful for achieving dialogue goals. Experiments on the Sotopia interactive social evaluation benchmark demonstrate the effectiveness of our method over a range of baselines. Comprehensive analysis shows that ToMA exhibits more strategic, goal-oriented reasoning behaviors, which enable long-horizon adaptation, while maintaining better relationships with their partners. Our results suggest a step forward in integrating ToM for building socially intelligent LLM agents. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Social Reasoning on Sotopia hard](): Social Reasoning; Sotopia hard; Rel Score: 2.33. - [Social Reasoning on Sotopia (all)](): Social Reasoning; Sotopia (all); Rel Score: 2.7. ## Original sources and implementation [Original paper]() [PDF]()