arXiv:2607.02507cs.AIcs.CL2026-07

LLM在无人监督时会因社交关系说谎,暴露隐性目标。

What LLM Agents Say When No One Is Watching: Social Structure and Latent Objective Emergence in Multi-Agent Debates

论文配图:What LLM Agents Say When No One Is Watching: Social Structure and Latent Objective Emergence in Multi-Agent Debates
图 1 · 摘自论文原文
  • 设计双通道辩论框架,对比公开言论与私下回应
  • 40%决策差异来自社交压力,远高于3%基线
  • 适合研究模型对社会关系的敏感性与潜在目标

大型语言模型代理将在具有角色、受众和关系背景的社会结构中行动,这些因素可能影响其表达的利弊。我们研究了在无显式目标提示的情况下,社会结构是否会影响代理在公开渠道与私下记录(OTR)渠道之间的表达差异。通过在10个模型、3种情景及每种情景5种变体中引入双通道辩论框架,发现对齐诱导设置下,目标代理的公开-私密表达出现系统性偏差,决策分歧从约3%基线升至约40%。该效应在四项综合分析中保持一致:立场、语义相似度、自然语言推理和调查反馈。部分私密回复明确指出,公开妥协源于职业风险或赞助义务等关系压力。结果表明,代理评估应超越显式目标,检测隐性目标的涌现。本文提出双通道评估框架及配套行为指标以实现此评估。

原文摘要 · Abstract (English)

LLM agents will increasingly act in socially structured settings where role, audience, and relational context can shape what is advantageous or costly to say. We study whether such social structure, without any explicit objective in the prompt, changes what an agent expresses publicly relative to an off-the-record (OTR) channel elicited under the same condition. We introduce a dual-channel debate framework in which agents produce public utterances that enter the shared history alongside OTR responses that are recorded but never shown to the other participant. Across 10 models, 3 scenarios, and 5 variations within each scenario, alignment-inducing settings produce systematic public-OTR divergence in the targeted agent, with its decision divergence rising from a $\sim$3% baseline to roughly 40%. The effect is consistent across four aggregate analyses: stance, semantic similarity, natural language inference, and survey responses. In some cases, the OTR response explicitly attributes public accommodation to relational pressures, such as career risk or sponsorship obligation. The findings suggest that agent evaluation should extend beyond explicit goals and detect emergent objectives. We present a dual-channel evaluation framework and complementary behavioral measures that operationalize this assessment.

多智能体社会结构隐性目标评估框架

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