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Zhongxin Liu

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#natural language process... Jul 2026

SynH-Rank: Quality-Aware Code Search via Diverse Data Synthesis and Hierarchical Ranking Training

SynH-Rank is proposed, a quality-aware code reranking framework that combines LLM-driven diverse data synthesis with hierarchical ranking training and employs a three-level labeling scheme to explicitly model the hierarchy: high-quality relevant>low-quality relevant>irrelevant.

Keyu Liang, Haoye Wang, Yanfu Yan et al. · arXiv.org · 0 citations