论主题匹配对比基线在多方向拒绝消除中的失效 / On the Failure of Topic-Matched Contrast Baselines in Multi-Directional Refusal Abliteration
1️⃣ 一句话总结
这篇论文发现,在消除AI模型拒绝回答有害指令的能力时,使用与有害主题相匹配的‘无害’指令作为对比基线,反而无法提取出有效的‘拒绝方向’,导致消除失败,揭示了对比基线设计的关键性。
Inasmuch as the removal of refusal behavior from instruction-tuned language models by directional abliteration requires the extraction of refusal-mediating directions from the residual stream activation space, and inasmuch as the construction of the contrast baseline against which harmful prompt activations are compared has been treated in the existing literature as an implementation detail rather than a methodological concern, the present work investigates whether a topically matched contrast baseline yields superior refusal directions. The investigation is carried out on the Qwen~3.5 2B model using per-category matched prompt pairs, per-class Self-Organizing Map extraction, and Singular Value Decomposition orthogonalization. It was found that topic-matched contrast produces no functional refusal directions at any tested weight level on any tested layer, while unmatched contrast on the same model, same extraction code, and same evaluation protocol achieves complete refusal elimination on six layers. The geometric analysis of the failure establishes that topic-matched subtraction cancels the dominant activation component shared between harmful and harmless prompts of the same subject, reducing the extracted direction magnitude below the threshold at which weight-matrix projection perturbs the residual stream. The implications for the design of contrast baselines in abliteration research are discussed.
论主题匹配对比基线在多方向拒绝消除中的失效 / On the Failure of Topic-Matched Contrast Baselines in Multi-Directional Refusal Abliteration
这篇论文发现,在消除AI模型拒绝回答有害指令的能力时,使用与有害主题相匹配的‘无害’指令作为对比基线,反而无法提取出有效的‘拒绝方向’,导致消除失败,揭示了对比基线设计的关键性。
源自 arXiv: 2603.22061