3 papers
cs.SE2025
Effective Code Membership Inference for Code Completion Models via Adversarial Prompts
Yuan Jiang, Zehao Li, Shan Huang +3
Membership inference attacks (MIAs) on code completion models offer an effective way to assess privacy risks by inferring whether a given code snippet was part of the training data…
cs.SE2025
Enhancing the Non-Functional Quality Compliance of LLM-Generated Code through Quality-Aware Preference Learning
Yuan Jiang, Yujian Zhang, Liang Lu +7
Large Language Models (LLMs) have been widely adopted in commercial code completion engines, significantly enhancing coding efficiency and productivity. However, even functionally…
cs.CR2024
StagedVulBERT: Multi-Granular Vulnerability Detection with a Novel Pre-trained Code Model
Yuan Jiang, Yujian Zhang, Xiaohong Su +2
The emergence of pre-trained model-based vulnerability detection methods has significantly advanced the field of automated vulnerability detection. However, these methods still fac…