11 papers
Breaking the Code: Security Assessment of AI Code Agents Through Systematic Jailbreaking Attacks
Shoumik Saha, Jifan Chen, Sam Mayers +3
Code-capable large language model (LLM) agents are embedded in software engineering workflows where they can read, write, and execute code, raising "jailbreak" stakes beyond text-o…
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…
SpecAgent: A Speculative Retrieval and Forecasting Agent for Code Completion
George Ma, Anurag Koul, Qi Chen +6
Large Language Models (LLMs) excel at code-related tasks but often struggle in realistic software repositories, where project-specific APIs and cross-file dependencies are crucial.…
Empowering Multi-Turn Tool-Integrated Agentic Reasoning with Group Turn Policy Optimization
Yifeng Ding, Hung Le, Songyang Han +5
Training Large Language Models (LLMs) for multi-turn Tool-Integrated Reasoning (TIR) - where models iteratively reason, generate code, and verify through execution - remains challe…
CODESTRUCT: Code Agents over Structured Action Spaces
Myeongsoo Kim, Joe Hsu, Dingmin Wang +3
LLM-based code agents treat repositories as unstructured text, applying edits through brittle string matching that frequently fails due to formatting drift or ambiguous patterns. W…
CodeScout: Contextual Problem Statement Enhancement for Software Agents
Manan Suri, Xiangci Li, Mehdi Shojaie +5
Current AI-powered code assistance tools often struggle with poorly-defined problem statements that lack sufficient task context and requirements specification. Recent analysis of…