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Gang Zhao

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Conference Open access 2026

LoRE: Enhancing Search Relevance with Progressive Chain-of-Thought and Preference Alignment

This paper proposes LoRE, a novel two-stage training framework for e-commerce search relevance, which outperforms GPT-5 by 29.1% in Macro-F1 and achieving a relative 27% online gain, offering a vital reference for industrial domain-specific post-training post-training.

Chenji Lu, Zhuo Chen, Hui Zhao et al. · 0 citations