Papers by Guowei Peng
OASIS: Mitigating Harmful Fine-tuning Attacks on LLMs via Orthogonal and Adaptive Safety Alignment Strategy (2026.acl-long)
Copied to clipboard
| Challenge: | Existing methods to decouple safety enforcement from harmful feature acquisition rely on perturbation directions that conflict with harmful gradients . harmful fine-tuning attacks pose a significant challenge for service providers aiming to uphold rigorous safety standards. |
| Approach: | They propose an orthogonal and ad hoc safety alignment strategy to decouple safety enforcement from harmful feature acquisition. |
| Outcome: | Experiments on four large language models show that OASIS reduces the Harmful Score by 60% compared to baselines while maintaining stable task utility. |