5 papers
Tool Specifications Matter: Uncovering and Mitigating Safety Risks in AI Agents
Minghui Pan, Jiayuxuan Yang, Yuanyuan Yuan +2
AI agents extend large language models (LLMs) with external tools, enabling them to perform complex tasks and translate model outputs into consequential real-world actions. Yet LLM…
Evaluating Privilege Usage of Agents with Real-World Tools
Quan Zhang, Lianhang Fu, Lvsi Lian +5
Equipping LLM agents with real-world tools can substantially improve productivity. However, granting agents autonomy over tool use also transfers the associated privileges to both…
Emergent Social Intelligence Risks in Generative Multi-Agent Systems
Yue Huang, Yu Jiang, Wenjie Wang +12
Multi-agent systems composed of large generative models are rapidly moving from laboratory prototypes to real-world deployments, where they jointly plan, negotiate, and allocate sh…
LSPRAG: LSP-Guided RAG for Language-Agnostic Real-Time Unit Test Generation
Gwihwan Go, Quan Zhang, Chijin Zhou +2
Automated unit test generation is essential for robust software development, yet existing approaches struggle to generalize across multiple programming languages and operate within…
Inducing Vulnerable Code Generation in LLM Coding Assistants
Binqi Zeng, Quan Zhang, Chijin Zhou +3
Due to insufficient domain knowledge, LLM coding assistants often reference related solutions from the Internet to address programming problems. However, incorporating external inf…