The conformity bias exhibited by large language models (LLMs) can pose a significant challenge to decision-making in LLM-based multi-agent systems (LLM-MAS). While many prior studies have treated "conformity" simply as a matter of opinion change, this study introduces the social psychological distinction between informational conformity and normative conformity in order to understand LLM conformity at the mechanism level. Specifically, we design new tasks to distinguish between informational conformity, in which participants in a discussion are motivated to make accurate judgments, and normative conformity, in which participants are motivated to avoid conflict or gain acceptance within a group. We then conduct experiments based on these task settings. The experimental results show that, among the six LLMs evaluated, up to five exhibited tendencies toward not only informational conformity but also normative conformity. Furthermore, intriguingly, we demonstrate that by manipulating subtle aspects of the social context, it may be possible to control the target toward which a particular LLM directs its normative conformity. These findings suggest that decision-making in LLM-MAS may be vulnerable to manipulation by a small number of malicious users. In addition, through analysis of internal vectors associated with informational and normative conformity, we suggest that although both behaviors appear externally as the same form of "conformity," they may in fact be driven by distinct internal mechanisms. Taken together, these results may serve as an initial milestone toward understanding how "norms" are implemented in LLMs and how they influence group dynamics.

翻译：大型语言模型（LLMs）表现出的从众偏差，对基于LLM的多智能体系统（LLM-MAS）中的决策制定构成了重大挑战。虽然许多先前研究将“从众”仅视为意见改变的问题，但本研究引入了社会心理学中信息性从众与规范性从众的区分，旨在从机制层面理解LLM的从众行为。具体而言，我们设计了新任务来区分：信息性从众（讨论参与者受动机驱动以做出准确判断）与规范性从众（参与者受动机驱动以避免冲突或获得群体接纳）。随后，我们基于这些任务设置开展了实验。实验结果表明，在评估的六种LLM中，多达五种不仅表现出对信息性从众的倾向，还表现出对规范性从众的倾向。此外，有趣的是，我们证明通过操纵社会情境的细微方面，可能控制特定LLM将其规范性从众指向的目标。这些发现表明，LLM-MAS中的决策制定可能易受少数恶意用户操纵。同时，通过对与信息性和规范性从众相关的内部向量进行分析，我们提出虽然这两种行为在外部表现为相同形式的“从众”，但它们实际上可能由不同的内部机制驱动。综合来看，这些结果可作为理解“规范”如何在LLM中实现及其如何影响群体动态的初步里程碑。