Recommender Systems
Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation
·3963 words·19 mins·
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🤗 Daily Papers
Machine Learning
Recommender Systems
🏢 Gaoling School of Artificial Intelligence, Renmin University of China
ReaRec: Unleashing latent reasoning power for sequential recommendation through inference-time multi-step reasoning.
OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment
·1937 words·10 mins·
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AI Generated
🤗 Daily Papers
Machine Learning
Recommender Systems
🏢 KuaiShou Inc.
OneRec: A unified generative model that replaces the traditional retrieve-and-rank strategy, significantly improving recommendation quality in real-world scenarios.
LLM-based User Profile Management for Recommender System
·2332 words·11 mins·
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AI Generated
🤗 Daily Papers
Machine Learning
Recommender Systems
🏢 Ulsan National Institute of Science and Technology
PURE: LLM-driven user profile management boosts recommendation by harnessing user reviews for personalized insights while tackling token limits. PURE enhances LLMs for better recommendations.