collaborators

6 papers

cs.SE2025

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…

cs.SE2025

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…

cs.LG2025

GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning

Zhen Xiang, Linzhi Zheng, Yanjie Li +9

The rapid advancement of large language model (LLM) agents has raised new concerns regarding their safety and security. In this paper, we propose GuardAgent, the first guardrail ag…

cs.CL2025

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…

cs.SE2024

RedCode: Risky Code Execution and Generation Benchmark for Code Agents

Chengquan Guo, Xun Liu, Chulin Xie +5

With the rapidly increasing capabilities and adoption of code agents for AI-assisted coding, safety concerns, such as generating or executing risky code, have become significant ba…

cs.CL2024

Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Bowen Jin, Chulin Xie, Jiawei Zhang +8

Large language models (LLMs), while exhibiting exceptional performance, suffer from hallucinations, especially on knowledge-intensive tasks. Existing works propose to augment LLMs…