Jigang Wang

AsFT: Anchoring Safety During LLM Fine-Tuning Within Narrow Safety Basin

Fine-tuning large language models (LLMs) improves performance but introduces critical safety vulnerabilities: even minimal harmful data can severely compromise safety measures. We observe that perturbations orthogonal to the alignment direction—defined by weight differences between aligned (safe) an