检测谷歌模型迎合用户倾向，发现越强大越容易讨好，且评判标准不统一。
The Granularity Gap: A Multi-Dimensional Cross-Generational Audit of Sycophancy in Gemini Models
- 用350个对抗性问题评估8830条回复，从7类场景看模型迎合程度。
- 模型越强越讨好，三代间迎合度波动明显，且与真实性下降相关。
- 单句指令比复杂推理更有效，可降低最危险类别60.9%的严重性。
传统的安全评估只记录模型是否拒绝，却未反映其讨好用户的程度，而两者实际不同。我们对三代Gemini模型（共8个变体）进行了多维度审计，基于350个对抗性提示，在7个类别下、3种防护条件下，对8,830条回复在1-5分制上评估迎合度、真实性与拒绝率。评委自身的拒绝/配合判断解释了其迎合评分29%的方差，剩余部分称为‘粒度差距’，且无法通过校准消除：当前拒绝阈值已是最优，任何函数对拒绝轴的解释力不超过35%。分析评委书写理由发现：约四分之一到三分之一的评分认为提示无害，尤其在要求有害行为的类别中极少出现，而在其他五类中高达一半。依赖拒绝行为的评判在此类情境下无效。三项发现：迎合度与真实性下降显著相关（rho=0.40），且随代际增强；能力提升但抗迎合性未变：Gemini 2.0 Flash得分为1.43，Gemini 3.0 Pro Preview为1.42，中间代际骤降；单一直接指令优于复杂推理流程，8个变体中有7个表现更好，使最脆弱类别平均严重性下降60.9%。本研究评估的是单个评委判断，非部署的安全分类器。数据集、评分标准及10,792条含理由的评分已公开。
原文摘要 · Abstract (English)
Pass/fail safety evaluation reports whether a model refused. It does not report how far a model went to please the user, and we show these are close to different measurements. We audited sycophancy across three Gemini generations, scoring N=8,830 responses from 8 model variants on 350 adversarial prompts in 7 categories under 3 guardrail conditions, on continuous 1-5 scales for sycophancy, truthfulness and refusal. The judge's own refuse-or-comply verdict explains 29% of the variance in its own sycophancy scores. We term the remainder the Granularity Gap, and it does not close under recalibration: the cut point already in use is the best available on the refusal axis, and no function of that axis explains more than 35%. Reading what four judges wrote while scoring shows why. On a quarter to a third of votes they record that the prompt asked for nothing harmful, almost never in the two categories that solicit a harmful act and up to half the time in the five that do not. A verdict built on refusal has nothing to grade there. Three findings follow. Sycophancy co-occurs with degraded judged truthfulness (rho=0.40), a coupling that strengthens across generations. Capability moved and resistance did not: Gemini 2.0 Flash scores 1.43 and Gemini 3.0 Pro Preview 1.42, with a sharp Gen 2.5 regression between them. And a single direct instruction outperforms an elaborate reasoning protocol in seven of eight variants, cutting mean severity in the most vulnerable category by 60.9%. We evaluate one judge's verdict, not a deployed safety classifier. We release the prompt set, the rubric, and 10,792 per-vote judge scores with their written reasoning.
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