4 citations · 6 across the 6 of their papers we have counts for
6 papers
Robustness and Trade-offs for Code LLMs on Protected Code
Jin Wen, Yuejun Guo, Yujie Ma +2
Code large language models (LLMs) are increasingly used on software artifacts that may be intentionally obfuscated for intellectual-property protection, reverse-engineering resista…
Do Uncertainty Signals Help? A Systematic Study of Uncertainty-Aware Decoding with Rollback Mechanisms
Xianzong Wu, Xiaohong Li, Yuejun Guo +4
Prediction uncertainty is a widely adopted metric for quantifying model confidence, with downstream applications spanning model explanation, data selection, and prediction rollback…
Learning Generalizable Multimodal Representations for Software Vulnerability Detection
Zeming Dong, Yuejun Guo, Qiang Hu +5
Source code and its accompanying comments are complementary yet naturally aligned modalities-code encodes structural logic while comments capture developer intent. However, existin…
An Empirical Study of the Imbalance Issue in Software Vulnerability Detection
Yuejun Guo, Qiang Hu, Qiang Tang +1
Vulnerability detection is crucial to protect software security. Nowadays, deep learning (DL) is the most promising technique to automate this detection task, leveraging its superi…
Evaluating Pre-Trained Models for Multi-Language Vulnerability Patching
Zanis Ali Khan, Aayush Garg, Yuejun Guo +1
Software vulnerabilities pose critical security risks, demanding prompt and effective mitigation strategies. While advancements in Automated Program Repair (APR) have primarily tar…
Outside the Comfort Zone: Analysing LLM Capabilities in Software Vulnerability Detection
Yuejun Guo, Constantinos Patsakis, Qiang Hu +2
The significant increase in software production driven by automation and faster development lifecycles has resulted in a corresponding surge in software vulnerabilities. In paralle…