SOTOPIA-π: Interactive Learning of Socially Intelligent Language Agents
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
Humans learn social skills through both imitation and social interaction. This social learning process is largely understudied by existing research on building language agents. Motivated by this gap, we propose an interactive learning method, SOTOPIA-π, improving the social intelligence of language agents. This method leverages behavior cloning and self-reinforcement training on filtered social interaction data according to large language model (LLM) ratings. We show that our training method allows a 7B LLM to reach the social goal completion ability of an expert model (GPT-4-based agent), while improving the safety of language agents and maintaining general QA ability on the MMLU benchmark. We also find that this training paradigm uncovers some difficulties in LLM-based evaluation of social intelligence: LLM-based evaluators overestimate the abilities of the language agents trained specifically for social interaction.
Key facts. Cited by 93 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 42 of its 61 references that are in the map. First posted on arXiv 13 Mar 2024.
Builds on
42 of 61 references.
References · 42
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Citing papers per year: 2024: 18; 2025: 34; 2026: 41.
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- 2026SmartSalesBench: A Resistance-Aware Multi-Turn Benchmark for Evaluating LLM Sales Agents9 Oct 2026
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- 2026At Equal Inference Cost, Multi-Agent Structure Does Not Beat a Single Frozen Agent25 Jun 2026
- 2026Can Agents Read the Room? Benchmarking Visual Social Intelligence in Multimodal Simulation13 Jun 2026
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- 2026CollabSim: A CSCW-Grounded Methodology for Investigating Collaborative Competence of LLM Agents through Controlled Multi-Agent Experiments4 Jun 2026
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- 2026Dual-Agent Co-Training for Health Coaching via Implicit Adversarial Preference Optimization7 May 2026
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- 2026IB-RL: Isolated Bilateral Reinforcement Learning for Strategic Dialogue Agents7 Aug 2026
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- 2026Evaluating LLM-as-a-Judge Beyond Score Alignment: A Psychometric Analysis of Residual Judging Difficulty2 Oct 2026
- 2026Towards Communication-Efficient Social Intelligence in Language Agents28 Sep 2026
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- 2026Mind2Dialogue: Training Human-Aware Language Models by Simulating User Mental States14 Sep 2026
- 2026Towards Better Agents for Multi-Turn User Interaction: The Next User Turn Is More Than Context18 Aug 2026
- 2026How Should I Pick a Foundation Model for My Robot? In Favor of a Community Evaluation Framework for Social Robots7 Aug 2026
- 2026The Judgment-Consequence Gap: LLM Moral Reasoning in Healthcare Decisions6 Aug 2026
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- 2026NICE: A Theory-Grounded Diagnostic Benchmark for Social Intelligence of LLMs28 May 2026
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