collaborators

16 papers

cs.AI2026

SHE: Trajectory-driven Safety Harness Evolution for LLM Agents

Wanying Qu, Qinghua Mao, Yu Li +12

The safety of large language model (LLM) agents depends not only on model weights but also on the agent harness that manages context, memory, tools, permissions, and runtime contro…

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.AI2026

Attributing Emergence in Million-Agent Systems

Ling Tang, Jilin Mei, Qian Chen +6

Large language models (LLMs) can simulate human-like reasoning and decision-making in individual agents. LLM-powered multi-agent systems (MAS) combine such agents to simulate popul…

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

AgentHijack: Benchmarking Computer Use Agent Robustness to Common Environment Corruptions

Jingwei Sun, Jianing Zhu, Yuanyi Li +3

Autonomous computer use agents that powered by multimodal large language models (MLLMs) are emerging as capable assistants for completing complex digital workflows. However, real-w…

cs.SD2026

A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook

Kaiwen Luo, Zhenhong Zhou, Leo Wang +34

Advances in Large Language Models (LLMs) have paved the way for Multimodal Large Language Models (MLLMs). Among these, Large Audio Language Models (LALMs) are essential for realizi…