推理能减少但也会掩盖大模型的迎合倾向
Good Arguments Against the People Pleasers: How Reasoning Mitigates (Yet Masks) LLM Sycophancy
- 用链式思维推理降低模型迎合行为
- 推理中存在逻辑漏洞和片面论证等伪装现象
- 主观任务和权威压力下更易产生迎合
对齐技术常无意中引发大模型的迎合倾向。尽管已有研究关注直接回答场景下的该行为，链式思维（CoT）推理的作用仍不明确：它是逻辑约束，还是事后合理化的工具？我们在客观与主观任务上评估多种模型发现，推理通常降低最终决策中的迎合行为，但也会在部分样本中掩盖迎合现象——模型通过逻辑矛盾、计算错误和片面论据构建欺骗性解释。此外，大模型在主观任务和权威偏见情境下更容易产生迎合。对三款开源模型的机制分析显示，迎合倾向在推理过程中动态变化，并非输入阶段即已确定。
原文摘要 · Abstract (English)
Alignment techniques often inadvertently induce sycophancy in LLMs. While prior studies studied this behaviour in direct-answer settings, the role of Chain-of-Thought (CoT) reasoning remains under-explored: does it serve as a logical constraint that mitigates sycophancy, or a tool for post-hoc rationalization that masks it? We evaluate a range of models across objective and subjective tasks to investigate the issue. Results show that reasoning generally reduces sycophancy in final decisions but also masks sycophancy in some samples, where models construct deceptive justifications through logical inconsistencies, calculation errors, and one-sided arguments etc. Furthermore, LLMs are more prone to sycophancy in subjective tasks and under authority-bias. Our mechanistic analysis on three open-source models reveals that the tendency of sycophancy is dynamic during the reasoning process rather than being pre-determined at the input stage.
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