5 citations · 10 across the 3 of their papers we have counts for
6 papers
Enhancing Code Vulnerability Detection via Vulnerability-Preserving Data Augmentation
Shangqing Liu, Wei Ma, Jian Wang +3
Source code vulnerability detection aims to identify inherent vulnerabilities to safeguard software systems from potential attacks. Many prior studies overlook diverse vulnerabilit…
Open-Source AI-based SE Tools: Opportunities and Challenges of Collaborative Software Learning
Zhihao Lin, Wei Ma, Tao Lin +7
Large Language Models (LLMs) have become instrumental in advancing software engineering (SE) tasks, showcasing their efficacy in code understanding and beyond. Like traditional SE…
Evaluating Large Language Models for Line-Level Vulnerability Localization
Jian Zhang, Chong Wang, Anran Li +4
Recently, Automated Vulnerability Localization (AVL) has attracted growing attention, aiming to facilitate diagnosis by pinpointing the specific lines of code responsible for vulne…
SoK: Comprehensive Analysis of Rug Pull Causes, Datasets, and Detection Tools in DeFi
Dianxiang Sun, Wei Ma, Liming Nie +1
Rug pulls pose a grave threat to the cryptocurrency ecosystem, leading to substantial financial loss and undermining trust in decentralized finance (DeFi) projects. With the emerge…
Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications
Wei Ma, Daoyuan Wu, Yuqiang Sun +5
Smart contracts are decentralized applications built atop blockchains like Ethereum. Recent research has shown that large language models (LLMs) have potential in auditing smart co…
LLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoning
Yuqiang Sun, Daoyuan Wu, Yue Xue +5
Large language models (LLMs) have demonstrated significant potential in various tasks, including those requiring human-level intelligence, such as vulnerability detection. However,…