6 papers
AgentCIScope: Grounded Contextual Integrity Evaluation for LLM Agents
Chengquan Guo, Zhaorun Chen, Zinan Lin +2
LLM agents are becoming increasingly capable of handling daily workspace tasks by interacting with application environments through tool calls. However, as agents read and write se…
SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations
Shuaiqi Wang, Aadyaa Maddi, Zinan Lin +1
Today, tool-calling agents are commonly evaluated or tested on static datasets of execution traces, including input commands, agent responses, and associated tool calls. However, i…
Emergent 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…
RedCodeAgent: Automatic Red-teaming Agent against Diverse Code Agents
Chengquan Guo, Chulin Xie, Yu Yang +6
Code agents have gained widespread adoption due to their strong code generation capabilities and integration with code interpreters, enabling dynamic execution, debugging, and inte…
BlueCodeAgent: A Blue Teaming Agent Enabled by Automated Red Teaming for CodeGen AI
Chengquan Guo, Yuzhou Nie, Chulin Xie +3
As large language models (LLMs) are increasingly used for code generation, concerns over the security risks have grown substantially. Early research has primarily focused on red te…
MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen +22
Multimodal foundation models (MMFMs) play a crucial role in various applications, including autonomous driving, healthcare, and virtual assistants. However, several studies have re…