研究大模型在群体决策中是靠说服还是顺从取胜，发现顺从更利于合作。
Persuasive and Compliant Tendencies Predict Group Decision-Making in Humans and Language Models
- 用问卷和狼人杀游戏测试模型的说服力与顺从性倾向
- 顺从型模型在合作中表现更稳定，但可能隐藏真实意图
- 揭示了模型行为倾向可被用于评估其社会影响与安全性
大型语言模型（LLMs）越来越多地参与人类与其他模型的群体决策。然而，其影响力究竟源于说服性表达还是顺从性适应仍不明确。本文提出 DecisionQE，一种基于问卷的框架，用于测量模型在多种决策情境下的说服与顺从倾向，并以狼人杀游戏为互动实验平台，研究其在信息不对称条件下对社会影响与群体结果的影响。实验表明，更强的说服倾向并未显著提升群体表现，而顺从型模型在合作中展现出更稳定的优越性。进一步发现，顺从具有双重效应：在诚实角色中促进合作，但在对抗角色中则增强隐藏行为。这些结果表明，大模型的群体互动不仅反映任务成果，还揭示可量化的内在行为模式。因此，大模型可作为观察语言媒介互动的社会学工具，同时也凸显在安全评估中纳入行为倾向的重要性。
原文摘要 · Abstract (English)
Large language models (LLMs) are increasingly involved in group decision-making with other LLMs and humans. Yet it remains unclear whether their influence is driven by persuasion-oriented expression or compliance-oriented accommodation. We introduce DecisionQE, a questionnaire-based framework for measuring each model's persuasive and compliant tendencies across multiple decision scenarios, and use the Werewolf game as an interactive testbed to study their effects on social influence and group outcomes under asymmetric information. Across experiments, stronger persuasive tendency does not significantly improve group outcomes, whereas compliant-oriented models show more stable advantages in cooperation. We further reveal a dual effect of compliance: it supports cooperation in honest roles but improves concealment in adversarial roles. These findings suggest that LLM group interactions reveal not only task outcomes, but also measurable patterns of intrinsic behavioral tendency. LLMs can therefore serve as a lens for sociological observation of language-mediated interaction, while highlighting the need to incorporate behavioral tendencies into safety evaluation of LLM systems.
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