Optimizing Generative Ranking Relevance via Reinforcement Learning in Xiaohongshu Search
Published:Nov 30, 2025 16:31
•1 min read
•ArXiv
Analysis
This article likely discusses the application of reinforcement learning to improve the relevance of search results in Xiaohongshu, a popular social media platform in China. The focus is on generative ranking, suggesting the use of models that generate ranked lists of results rather than simply retrieving them. The use of reinforcement learning implies an iterative process where the ranking model is trained to optimize for a specific reward, likely related to user engagement or satisfaction. The source being ArXiv indicates this is a research paper.
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