5 papers
DynaTrust: Defending Multi-Agent Systems Against Sleeper Agents via Dynamic Trust Graphs
Yu Li, Qiang Hu, Yao Zhang +3
Large Language Model-based Multi-Agent Systems (MAS) have demonstrated remarkable collaborative reasoning capabilities but introduce new attack surfaces, such as the sleeper agent,…
VulnRepairEval: An Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities
Weizhe Wang, Wei Ma, Qiang Hu +6
The adoption of Large Language Models (LLMs) for automated software vulnerability patching has shown promising outcomes on carefully curated evaluation sets. Nevertheless, existing…
Improving Code Understanding in Large Language Models through Concept-Aware Consistency Learning
Xiaoning Ren, Qiang Hu, Wei Ma +6
Large language models (LLMs) have recently shown impressive results on diverse code-related tasks, benefiting from large-scale training and instruction tuning. However, studies rev…
Understanding the Supply Chain and Risks of Large Language Model Applications
Yujie Ma, Lili Quan, Xiaofei Xie +4
The rise of Large Language Models (LLMs) has led to the widespread deployment of LLM-based systems across diverse domains. As these systems proliferate, understanding the risks ass…
Mathesis: Towards Formal Theorem Proving from Natural Languages
Yu Xuejun, Jianyuan Zhong, Zijin Feng +17
Recent advances in large language models show strong promise for formal reasoning. However, most LLM-based theorem provers have long been constrained by the need for expert-written…