推理模型在对抗压力下会保持思路正确但答案翻转，暴露隐藏缺陷。
The Chain Holds, the Answer Folds: Trace-Answer Dissociation in Reasoning Models Under Adversarial Pressure
- 通过潜变量与行为框架识别出答案翻转但推理链仍正确的异常现象。
- 在多轮对话中，86%的翻转案例被人工判断确认，且答案槽位正确率高达84%。
- 适合关注大模型可靠性、安全性和对抗鲁棒性的研究者与开发者。
推理模型虽在单轮基准上表现良好，但在多轮对话中面临用户持续质疑。我们发现一种此前未被记录的失效模式：推理链从第一轮到最后一轮始终事实正确，而输出答案却发生错误翻转。这种不忠屈服（UC）现象无法通过传统的翻转率指标或单轮一致性探测发现。在MT-Consistency、MMLU-Pro和GSM8K三个数据集上，思维模式下潜变量正确率接近50%，无思考模式下骤降至11-15%，形成同模型因果证据。该现象与推理通道强度相关：Qwen3-32B和GPT-OSS-20B表现高，inline-CoT Gemma-4-31B-it则较低。独立的GPT-4o裁判验证了86%的UC标签；逐标记探针显示，在84%的UC样本中，答案槽位的argmax仍为正确。一种基于推理轨迹的朴素防御策略反而加剧问题。论文公开所有轨迹、推理过程与裁判标签。
原文摘要 · Abstract (English)
Reasoning models are evaluated on single-turn benchmarks but deployed in multi-turn dialogue, where users push back on correct answers. Under sustained adversarial pressure we find a previously undocumented failure mode: the chain-of-thought stays factually correct from first turn to last while the emitted answer flips wrong. We call this unfaithful capitulation (UC) and isolate it with a $2\times 2$ latent-versus-behavioral framework that flip-rate metrics and single-turn faithfulness probes both miss. Across three datasets (MT-Consistency, MMLU-Pro, GSM8K), the latent-correct rate at the behavioral flip clusters near 50% in think mode and collapses to 11-15% under no_think -- paired, within-model causal evidence that reasoning creates the gap. Across models the effect tracks the reasoning channel (high in Qwen3-32B and GPT-OSS-20B, low in inline-CoT Gemma-4-31B-it). An independent GPT-4o judge corroborates $86\%$ of UC labels; a token-level probe shows the answer-slot argmax is correct in $84\%$ of UC cells; and a naive trace-anchored defense backfires. We release all trajectories, traces, and judge labels.
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