collaborators

8 papers

cs.CL2026

An Early Warning of Emerging Biosecurity Risks in Frontier LLMs

Zhida He, Xia Hu, Baichen Le +20

Frontier large language models (LLMs) are increasingly integrated into scientific workflows, yet their growing biological capabilities may outpace current safeguards. To assess the…

cs.CR2026

SkillSafetyBench: Evaluating Agent Safety under Skill-Facing Attack Surfaces

Chang Jin, An Wang, Zeming Wei +7

Reusable skills are becoming a common interface for extending large language model agents, packaging procedural guidance with access to files, tools, memory, and execution environm…

cs.AI2026

Not All Turns Matter: Credit Assignment for Multi-Turn Jailbreaking

Zhida He, Xiaoyu Wen, Han Qi +7

Deploying LLMs in multi-turn dialogues facilitates jailbreak attacks that distribute harmful intent across seemingly benign turns. Recent training-based multi-turn jailbreak method…

cs.LG2026

Dynamic Adversarial Reinforcement Learning for Robust Multimodal Large Language Models

Yicheng Bao, Xuhong Wang, Qiaosheng Zhang +3

Despite their impressive capabilities, Multimodal Large Language Models (MLLMs) exhibit perceptual fragility when confronted with visually complex scenes. This weakness stems from…

cs.AI2026

MAGIC: A Co-Evolving Attacker-Defender Adversarial Game for Robust LLM Safety

Xiaoyu Wen, Zhida He, Han Qi +7

Ensuring robust safety alignment is crucial for Large Language Models (LLMs), yet existing defenses often lag behind evolving adversarial attacks due to their \textbf{reliance on s…

cs.LG2026

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…