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TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance

arXiv — cs.CL•Thursday, November 13, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
The publication of TaoSR-AGRL on arXiv marks a significant advancement in e-commerce search relevance, particularly for platforms like Taobao. As AI-powered shopping becomes more prevalent, the ability to accurately predict query-product relevance is crucial for enhancing user experience and driving business conversions. Traditional methods have struggled with complex queries and long-tail cases, often lacking robust reasoning capabilities. TaoSR-AGRL introduces innovative solutions such as Rule-aware Reward Shaping and Adaptive Guided Replay, which aim to improve the effectiveness of large language models in this context. By addressing the challenges faced by existing reinforcement learning strategies, this framework represents a promising step forward in optimizing search relevance in e-commerce, potentially transforming how users interact with online shopping platforms.
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