Large Language Model (LLM)-based agents are increasingly used for software engineering tasks, yet their performance is not determined by the base model alone. The agent harness substantially shapes how SE agents interact with repositories, execute actions, and validate solutions. However, the role of harness design rem...
Hai-Chuan Hu, Quan-Jun Zhang, Sheng-Cheng Yu et al.· 2 citations
MultiFixer, a novel Coordinator-Proposer based multi-agent framework for multi-hunk repair, performs tool-augmented bug analysis, constructs fine-grained repair context, iteratively generates patches through a Coordinator-Proposer architecture, and applies two-stage patch refinement for syntactic and semantic correctne...
Hai-Chuan Hu, Chun-Rong Fang, Ye Shang et al.· arXiv.org· 0 citations
This work introduces relation-aware emotional support conversation, a new task that evaluates whether LLMs can capture and utilize the evolving dynamics of relationships to offer more effective emotional support.
Hai-Chuan Hu, Yang Xiao, Ming-Ni Tang et al.· 0 citations
ReProAgent is a multi-stage agent framework for reproduction test generation from issue reports that decomposes the task into four agent stages: bug localization, root cause analysis, test planning, and test generation, and generalizes across multiple backbone LLMs.
Quanjun Zhang, Yi Zheng, Ye Shang et al.· 1 citation
This survey aims to clarify the conceptual boundaries of self-evolving coding agents and provide a foundation for designing more adaptive, reliable, and software-aware agentic systems.
Hao Zhou, Hai-Chuan Hu, Tianyu Luo et al.· 0 citations
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