To improve large language models'ability to resolve real-world software issues, prior work has focused on constructing large-scale agent trajectory datasets and performing supervised fine-tuning (SFT) on successful trajectories. However, task success does not guarantee high-quality supervision: successful trajectories...
De-Wu Zheng, Rui Ye, Yanlan Wang et al.· 3 citations
PTA-IRT is proposed, a Privileged Trajectory-Aware Item Response Theory framework that fuses process and outcome signals and consistently outperforms prior IRT baselines on score and ranking recovery across four SWE benchmarks.
Ke-Feng Duan, De-Wu Zheng, Yan-Lin Wang et al.· 0 citations
ACToR identifies critical tokens during generation and triggers targeted retrieval on demand to provide repository context at these decisive positions, and designs a position-aware weighting method for dense retrievers to prioritize context that is more informative for generation.
Ke-Feng Duan, De-Wu Zheng, Yan-Lin Wang et al.· 0 citations
MCR-Bench is introduced, the first defect state-aware benchmark designed for realistic multi-round code review, and in-depth error analysis dissects the distinct drivers of false positives and false negatives, revealing critical weaknesses such as cross-round temporal misalignment and inadequate long-range memory.
De-Wu Zheng, Yan-Lin Wang, Xi-Wen Wang et al.· Proceedings of the ACM on So...· 1 citation
PhoenixRepair is a multi-agent framework that systematically explores multiple candidate edit locations and performs iterative reflection and refinement on patch generation, thereby expanding the search space of repair strategies and achieves higher fault localization accuracy than existing approaches.
Tian-Yue Jiang, Yan-Lin Wang, Xin He et al.· arXiv.org· 2 citations
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