most citedLLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoning

19 citations · 38 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.SE2024★ 3 cited

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…

cs.SE2024★ 3 cited

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…

cs.SE2024★ 5 cited

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…

cs.SE2024★ 6 cited

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…

cs.SE2023

Exploring Code Analysis: Zero-Shot Insights on Syntax and Semantics with LLMs

Wei Ma, Zhihao Lin, Shangqing Liu +8

Code analysis is fundamental in Software Engineering, supporting debugging, optimization, and security assessment. Human developers approach it through syntax parsing, static seman…