activity
20232026
most citedExploring the Potential of ChatGPT in Automated Code Refinement: An Empirical Study

9 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR2026

From Component Manipulation to System Compromise: Understanding and Detecting Malicious MCP Servers

Yiheng Huang, Zhijia Zhao, Bihuan Chen +5

The model context protocol (MCP) standardizes how LLMs connect to external tools and data sources, enabling faster integration but introducing new attack vectors. Despite the growi…

cs.SE2026

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code

Kaifeng He, Xiaojun Zhang, Peiliang Cai +7

Large language models (LLMs) frequently generate defective outputs in code generation tasks, ranging from logical bugs to security vulnerabilities. While these generation failures…

cs.AI2024

A general approach to enhance the survivability of backdoor attacks by decision path coupling

Yufei Zhao, Dingji Wang, Bihuan Chen +2

Backdoor attacks have been one of the emerging security threats to deep neural networks (DNNs), leading to serious consequences. One of the mainstream backdoor defenses is model re…

cs.SE20239 cited

Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical Study

Qi Guo, Junming Cao, Xiaofei Xie +4

Code review is an essential activity for ensuring the quality and maintainability of software projects. However, it is a time-consuming and often error-prone task that can signific…

cs.CR2023

Killing Two Birds with One Stone: Malicious Package Detection in NPM and PyPI using a Single Model of Malicious Behavior Sequence

Junan Zhang, Kaifeng Huang, Yiheng Huang +4

Open-source software (OSS) supply chain enlarges the attack surface, which makes package registries attractive targets for attacks. Recently, package registries NPM and PyPI have b…