1 citations · 1 across the 9 of their papers we have counts for
11 papers
Semantic Consensus Decoding: Backdoor Defense for Verilog Code Generation
Guang Yang, Xing Hu, Xiang Chen +1
Large language models (LLMs) for Verilog code generation are increasingly adopted in hardware design, yet remain vulnerable to backdoor attacks where adversaries inject malicious t…
DepRadar: Agentic Coordination for Context Aware Defect Impact Analysis in Deep Learning Libraries
Yi Gao, Xing Hu, Tongtong Xu +3
Deep learning libraries like Transformers and Megatron are now widely adopted in modern AI programs. However, when these libraries introduce defects, ranging from silent computatio…
Actionable Warning Is Not Enough: Recommending Valid Actionable Warnings with Weak Supervision
Zhipeng Xue, Zhipeng Gao, Tongtong Xu +3
The use of static analysis tools has gained increasing popularity among developers in the last few years. However, the widespread adoption of static analysis tools is hindered by t…
HFuzzer: Testing Large Language Models for Package Hallucinations via Phrase-based Fuzzing
Yukai Zhao, Menghan Wu, Xing Hu +1
Large Language Models (LLMs) are widely used for code generation, but they face critical security risks when applied to practical production due to package hallucinations, in which…
An Empirical Study of Vulnerable Package Dependencies in LLM Repositories
Shuhan Liu, Xing Hu, Xin Xia +2
Large language models (LLMs) have developed rapidly in recent years, revolutionizing various fields. Despite their widespread success, LLMs heavily rely on external code dependenci…
Clean Code, Better Models: Enhancing LLM Performance with Smell-Cleaned Dataset
Zhipeng Xue, Xiaoting Zhang, Zhipeng Gao +4
The Large Language Models (LLMs) have demonstrated great potential in code-related tasks. However, most research focuses on improving the output quality of LLMs (e.g., correctness)…