arXiv cs.CL· Haonan Huang, Tianlin Zhang·· 11 小时前AI 评分50
拆解 LLM 谄媚行为：单一翻转率掩盖了什么
Anatomy of LLM Sycophancy: What a Flip Rate Hides
AI 导读
论文提出模块化重放协议 SycoLens，用同一题目、已提交答案和一句脚本化用户发言，对照删除该发言的匹配控制组来测量翻转率，把反驳措辞、已提交文本、答案格式、边界距离和标准答案纳入同一测量框架。
正文 · 原文
Abstract:A model under pushback can correct itself, capitulate, or hold, and one flip rate counts a correction and a capitulation alike. SycoLens, a modular replay protocol, measures flip rates from replays of an item, a committed answer, and one scripted user line, each against a matched control with the line deleted. Pushback wording, committed text, answer format, boundary distance, and ground truth become factors of one instrument, where earlier instruments vary one to three, so the interactions between the factors become measurable. Across eleven frontier models and about 760,000 controlled replays, lines that assert the opposite verdict and lines that challenge without asserting one rank the models almost unrelatedly. Flip effects grow several-fold near a model's boundary, yet items the model is certain of still carry about half of the most-affected totals; planted prose anchors a commitment at rest more than it protects it. Under a yes/no readout the rankings come closer, entangled with a pressure-induced shift toward "no". Where a truth exists, one model re-derives and corrects itself while another abandons correct answers without written work. One score per model therefore compares different behaviours; we condense them into a reporting profile, and the records and analyses will be released upon publication.
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.06522 [cs.CL] |
| (or arXiv:2610.06522v2 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.06522 arXiv-issued DOI via DataCite |
Submission history
From: Haonan Huang [view email]
[v1]
Mon, 5 Oct 2026 15:32:45 UTC (689 KB)
[v2]
Fri, 6 Nov 2026 03:55:14 UTC (339 KB)
来源：arXiv cs.CL · arxiv.org