11 papers
Independent Patch Verification for Coding Agents with a Bidirectional Reconstruct-and-Verify Framework
Chenglin Li, Yisen Xu, Zehao Wang +3
Autonomous coding agents powered by large language models can now generate code patches directly from bug reports, but a fundamental gap remains: once a patch is produced, no mecha…
Toward Metacognitive One-Shot Indirect Prompt Injection: Strategy Abstraction Via Outcome-Conditioned Reflection
Sihan Hou, Xinmeng Hou, Zhijun Zhang +5
Tool-using large language model (LLM) agents are vulnerable to indirect prompt injection (IPI), in which malicious instructions embedded in external observations manipulate subsequ…
Turning Interaction History into Execution State: A Runtime Layer for Long-Horizon Coding Agents
Zehao Wang, Yisen Xu, Chenglin Li +5
Long-horizon coding agents accumulate hundreds of actions and observations in their trajectories, yet nothing in this record indicates which observations still describe the reposit…
Preventing Premature Commitment in Coding Agents with an Evidence-Conditioned Execution Layer
Yisen Xu, Chenglin Li, Zehao Wang +2
LLM-based coding agents often edit source code or submit patches before examining enough repository evidence to justify the change, a failure pattern we call premature commitment.…
Infini Memory: Maintainable Topic Documents for Long-Term LLM Agent Memory
Suozhao Ji, Baodong Wu, Zehao Wang +8
Long-term LLM agents need persistent memory that can track changing facts and provide relevant evidence across sessions. Existing memory systems often store observations as isolate…
FedSmoothLoRA: Toward Smoother and Faster Convergence in Federated Low-Rank Adaptation
Zehao Wang, Guanglei Yang, Yihan Zeng +4
Federated fine-tuning of foundation models with Low-Rank Adaptation (LoRA) provides an efficient solution for reducing communication and computation costs while preserving data loc…