3 citations · 6 across the 10 of their papers we have counts for
11 papers
Bash-Commenter: Leveraging Syntax-Aware Preference Optimization to Reinforce Large Language Model for Bash Code Comment Generation
Lei Yu, Jingyuan Zhang, Xin Wang +5
Bash script comprehension is challenging due to Bash's syntactic freedom and complex command structures. Despite its critical role in system administration, Bash scripts often lack…
BashCoder-R1: Towards Robust and Explainable Bash Code Generation with Robustness-Aware Group Relative Policy Optimization
Lei Yu, Peng Wang, Jia Xu +7
Bash scripts are critical for system administration, DevOps, and CI/CD, where code quality affects stability and security. However, LLM-generated scripts often lack reasoning and c…
ATLAS: Agentic Taxonomy of Large-Scale Software Ecosystems
Junyi Lu, Mengyao Lyu, Jiahui Wu +6
The open-source ecosystem on GitHub lacks a systematic hierarchical taxonomy of software repositories. GitHub Topics, the dominant organizational mechanism, is flat, inconsistent,…
SQL-Commenter: Aligning Large Language Models for SQL Comment Generation with Direct Preference Optimization
Lei Yu, Peng Wang, Jingyuan Zhang +6
SQL query comprehension is a significant challenge due to complex syntax, diverse join types, and deep nesting. Many queries lack adequate comments, severely hindering code readabi…
Towards Secure and Explainable Smart Contract Generation with Security-Aware Group Relative Policy Optimization
Lei Yu, Jingyuan Zhang, Xin Wang +3
Smart contracts automate the management of high-value assets, where vulnerabilities can lead to catastrophic financial losses. This challenge is amplified in Large Language Models…
SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection
Lei Yu, Shiqi Cheng, Zhirong Huang +6
With the increasing security issues in blockchain, smart contract vulnerability detection has become a research focus. Existing vulnerability detection methods have their limitatio…
Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detection
Lei Yu, Zhirong Huang, Hang Yuan +8
Smart contract vulnerability detection remains a major challenge in blockchain security. Existing vulnerability detection methods face two main issues: (1) Existing datasets lack c…
Towards Practical Defect-Focused Automated Code Review
Junyi Lu, Lili Jiang, Xiaojia Li +4
The complexity of code reviews has driven efforts to automate review comments, but prior approaches oversimplify this task by treating it as snippet-level code-to-text generation a…
MOS: Towards Effective Smart Contract Vulnerability Detection through Mixture-of-Experts Tuning of Large Language Models
Hang Yuan, Lei Yu, Zhirong Huang +7
Smart contract vulnerabilities pose significant security risks to blockchain systems, potentially leading to severe financial losses. Existing methods face several limitations: (1)…
DeepCRCEval: Revisiting the Evaluation of Code Review Comment Generation
Junyi Lu, Xiaojia Li, Zihan Hua +5
Code review is a vital but demanding aspect of software development, generating significant interest in automating review comments. Traditional evaluation methods for these comment…
Smart-LLaMA: Two-Stage Post-Training of Large Language Models for Smart Contract Vulnerability Detection and Explanation
Lei Yu, Shiqi Chen, Hang Yuan +7
With the rapid development of blockchain technology, smart contract security has become a critical challenge. Existing smart contract vulnerability detection methods face three mai…