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20232026
most citedWhat Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs?

89 citations · 104 across the 14 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.SE2024

EvalSVA: Multi-Agent Evaluators for Next-Gen Software Vulnerability Assessment

Xin-Cheng Wen, Jiaxin Ye, Cuiyun Gao +2

Software Vulnerability (SV) assessment is a crucial process of determining different aspects of SVs (e.g., attack vectors and scope) for developers to effectively prioritize effort…

cs.SE2024

Repository-Level Graph Representation Learning for Enhanced Security Patch Detection

Xin-Cheng Wen, Zirui Lin, Cuiyun Gao +3

Software vendors often silently release security patches without providing sufficient advisories (e.g., Common Vulnerabilities and Exposures) or delayed updates via resources (e.g.…

cs.SE2024★ 2 cited

VulEval: Towards Repository-Level Evaluation of Software Vulnerability Detection

Xin-Cheng Wen, Xinchen Wang, Yujia Chen +3

Deep Learning (DL)-based methods have proven to be effective for software vulnerability detection, with a potential for substantial productivity enhancements for detecting vulnerab…

cs.SE2024

SCALE: Constructing Structured Natural Language Comment Trees for Software Vulnerability Detection

Xin-Cheng Wen, Cuiyun Gao, Shuzheng Gao +2

Recently, there has been a growing interest in automatic software vulnerability detection. Pre-trained model-based approaches have demonstrated superior performance than other Deep…

cs.CR2024

ReposVul: A Repository-Level High-Quality Vulnerability Dataset

Xinchen Wang, Ruida Hu, Cuiyun Gao +3

Open-Source Software (OSS) vulnerabilities bring great challenges to the software security and pose potential risks to our society. Enormous efforts have been devoted into automate…

cs.SE2024

Game Rewards Vulnerabilities: Software Vulnerability Detection with Zero-Sum Game and Prototype Learning

Xin-Cheng Wen, Cuiyun Gao, Xinchen Wang +3

Recent years have witnessed a growing focus on automated software vulnerability detection. Notably, deep learning (DL)-based methods, which employ source code for the implicit acqu…