3 papers
cs.SE2026
Coherence Collapse: Diagnosing Why Code Agents Fail After Reaching the Right Code
Myeongsoo Kim, Dingmin Wang, Siwei Cui +6
Code agents resolve 65-70% of SWE-bench Verified issues, but Pass@1 cannot tell us why the rest fail, and, as we show, capable-model failures are systematically misdiagnosed withou…
cs.SE2025
Training Language Model Agents to Find Vulnerabilities with CTF-Dojo
Terry Yue Zhuo, Dingmin Wang, Hantian Ding +2
Large language models (LLMs) have demonstrated exceptional capabilities when trained within executable runtime environments, notably excelling at software engineering tasks through…
cs.CR2025
Cyber-Zero: Training Cybersecurity Agents without Runtime
Terry Yue Zhuo, Dingmin Wang, Hantian Ding +2
Large Language Models (LLMs) have achieved remarkable success in software engineering tasks when trained with executable runtime environments, particularly in resolving GitHub issu…