most citedSmart-LLaMA: Two-Stage Post-Training of Large Language Models for Smart Contract Vulnerability Detection and Explanation

3 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR2025

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…

cs.CR2025

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…

cs.CR2025

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…

cs.SE20252 cited

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)…

cs.CR20243 cited

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…