10 citations · 10 across the 5 of their papers we have counts for
5 papers
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…
Enhancing the Non-Functional Quality Compliance of LLM-Generated Code through Quality-Aware Preference Learning
Liang Lu, Yuan Jiang, Christoph Treude +4
Large Language Models (LLMs) have been widely adopted in commercial code completion engines, significantly enhancing coding efficiency and productivity. However, even functionally…
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…
Dynamically Relative Position Encoding-Based Transformer for Automatic Code Edit
Shiyi Qi, Yaoxian Li, Cuiyun Gao +4
Adapting Deep Learning (DL) techniques to automate non-trivial coding activities, such as code documentation and defect detection, has been intensively studied recently. Learning t…
VulSPG: Vulnerability detection based on slice property graph representation learning
Weining Zheng, Yuan Jiang, Xiaohong Su
Vulnerability detection is an important issue in software security. Although various data-driven vulnerability detection methods have been proposed, the task remains challenging si…