most citedA Survey of LLM-based Automated Program Repair: Taxonomies, Design Paradigms, and Applications

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Evaluating Coding Agents on Kernel Exploit Generation

Junyoung Jang, Gwanhyun Lee, Hwiwon Lee +4

Coding agents now find real vulnerabilities in production software. However, bug discovery results do not measure whether agents can construct exploit primitives. We introduce KEX-…

cs.CR2026

Agentic Vulnerability Reasoning on COTS Binaries

Hwiwon Lee, Jongseong Kim, Lingming Zhang

LLM agents have been increasingly adopted for solving security tasks. However, existing evaluations usually require source code access, while commercial off-the-shelf (COTS) binari…

cs.CR2026

Weaver: Fuzzing JavaScript Engines at the JavaScript-WebAssembly Boundary

Lingming Zhang, Binbin Zhao, Puzhuo Liu +4

The security of modern JavaScript (JS) engines is critical since they provide the primary defense mechanism for executing untrusted code on the web. The recent integration of WebAs…

cs.SE2025★ 2 cited

A Survey of LLM-based Automated Program Repair: Taxonomies, Design Paradigms, and Applications

Boyang Yang, Zijian Cai, Fengling Liu +5

Large language models (LLMs) are reshaping automated program repair. We present a reproducible hierarchical taxonomy that organizes 66 LLM-based repair systems according to where r…

cs.LG2025

SEC-bench: Automated Benchmarking of LLM Agents on Real-World Software Security Tasks

Hwiwon Lee, Ziqi Zhang, Hanxiao Lu +1

Rigorous security-focused evaluation of large language model (LLM) agents is imperative for establishing trust in their safe deployment throughout the software development lifecycl…