activity
20222026
most citedHow Far Have We Gone in Vulnerability Detection Using Large Language Models

10 citations · 21 across the 10 of their papers we have counts for

collaborators

11 papers

cs.SE2026

PCodeTrans: Translate Decompiled Pseudocode to Compilable and Executable Equivalent

Yuxin Cui, Zeyu Gao, Shuxian He +2

Decompilation is foundational to binary analysis, yet conventional tools prioritize human readability over strict recompilability and verifiable runtime correctness. While recent L…

cs.CR2026

SecCodeBench-V2 Technical Report

Longfei Chen, Ji Zhao, Lanxiao Cui +24

We introduce SecCodeBench-V2, a publicly released benchmark for evaluating Large Language Model (LLM) copilots' capabilities of generating secure code. SecCodeBench-V2 comprises 98…

cs.CR2025

Tady: A Neural Disassembler without Structural Constraint Violations

Siliang Qin, Fengrui Yang, Hao Wang +4

Disassembly is a crucial yet challenging step in binary analysis. While emerging neural disassemblers show promise for efficiency and accuracy, they frequently generate outputs vio…

cs.CR2025

Mono: Is Your "Clean" Vulnerability Dataset Really Solvable? Exposing and Trapping Undecidable Patches and Beyond

Zeyu Gao, Junlin Zhou, Bolun Zhang +4

The quantity and quality of vulnerability datasets are essential for developing deep learning solutions to vulnerability-related tasks. Due to the limited availability of vulnerabi…

cs.SE2025

DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios

Zeyu Gao, Yuxin Cui, Hao Wang +4

Decompilers are fundamental tools for critical security tasks, from vulnerability discovery to malware analysis, yet their evaluation remains fragmented. Existing approaches primar…

cs.SE2024

ViC: Virtual Compiler Is All You Need For Assembly Code Search

Zeyu Gao, Hao Wang, Yuanda Wang +1

Assembly code search is vital for reducing the burden on reverse engineers, allowing them to quickly identify specific functions using natural language within vast binary programs.…

cs.SE2024

CEBin: A Cost-Effective Framework for Large-Scale Binary Code Similarity Detection

Hao Wang, Zeyu Gao, Chao Zhang +4

Binary code similarity detection (BCSD) is a fundamental technique for various application. Many BCSD solutions have been proposed recently, which mostly are embedding-based, but h…

cs.SE2024

CLAP: Learning Transferable Binary Code Representations with Natural Language Supervision

Hao Wang, Zeyu Gao, Chao Zhang +7

Binary code representation learning has shown significant performance in binary analysis tasks. But existing solutions often have poor transferability, particularly in few-shot and…

cs.AI2023★ 10 cited

How Far Have We Gone in Vulnerability Detection Using Large Language Models

Zeyu Gao, Hao Wang, Yuchen Zhou +2

As software becomes increasingly complex and prone to vulnerabilities, automated vulnerability detection is critically important, yet challenging. Given the significant successes o…

cs.SE2023★ 4 cited

kTrans: Knowledge-Aware Transformer for Binary Code Embedding

Wenyu Zhu, Hao Wang, Yuchen Zhou +4

Binary Code Embedding (BCE) has important applications in various reverse engineering tasks such as binary code similarity detection, type recovery, control-flow recovery and data-…

cs.CR2022★ 7 cited

jTrans: Jump-Aware Transformer for Binary Code Similarity

Hao Wang, Wenjie Qu, Gilad Katz +5

Binary code similarity detection (BCSD) has important applications in various fields such as vulnerability detection, software component analysis, and reverse engineering. Recent s…