4 papers
RAPO: Risk-Aware Preference Optimization for Generalizable Safe Reasoning
Zeming Wei, Qiaosheng Zhang, Xia Hu +1
Large Reasoning Models (LRMs) have achieved tremendous success with their chain-of-thought (CoT) reasoning, yet also face safety issues similar to those of basic language models. I…
False Sense of Security: Why Probing-based Malicious Input Detection Fails to Generalize
Cheng Wang, Zeming Wei, Qin Liu +1
Large Language Models (LLMs) can comply with harmful instructions, raising serious safety concerns despite their impressive capabilities. Recent work has leveraged probing-based ap…
Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection
Chengcan Wu, Zeming Wei, Huanran Chen +2
While Large Language Models (LLMs) have demonstrated impressive performance in various domains and tasks, concerns about their safety are becoming increasingly severe. In particula…
Towards the Worst-case Robustness of Large Language Models
Huanran Chen, Yinpeng Dong, Zeming Wei +2
Recent studies have revealed the vulnerability of large language models to adversarial attacks, where adversaries craft specific input sequences to induce harmful, violent, private…