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- Tsinghua UniversityCN19 papers
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- OriginWater (China)CN12 papers
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- Renmin University of ChinaCN8 papers
- Chinese Academy of SciencesCN7 papers
- National University of SingaporeSG7 papers
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16 papers · 1 filter
Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation
Tianyu Zhu, Yansong Shi, Yuan Zhang +3
Modern recommender systems employ various sequential modules such as self-attention to learn dynamic user interests. However, these methods are less effective in capturing collabor…
LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting
Yimeng Bai, Yang Zhang, Jing Lu +5
Short video recommendations often face limitations due to the quality of user feedback, which may not accurately depict user interests. To tackle this challenge, a new task has eme…
Query-dominant User Interest Network for Large-Scale Search Ranking
Tong Guo, Xuanping Li, Haitao Yang +9
Historical behaviors have shown great effect and potential in various prediction tasks, including recommendation and information retrieval. The overall historical behaviors are var…
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems
Zhenghai Xue, Qingpeng Cai, Bin Yang +4
The field of Reinforcement Learning (RL) has garnered increasing attention for its ability of optimizing user retention in recommender systems. A primary obstacle in this optimizat…
RAMP: Retrieval-Augmented MOS Prediction via Confidence-based Dynamic Weighting
Hui Wang, Shiwan Zhao, Xiguang Zheng +1
Automatic Mean Opinion Score (MOS) prediction is crucial to evaluate the perceptual quality of the synthetic speech. While recent approaches using pre-trained self-supervised learn…
Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation
Yunzhu Pan, Chen Gao, Jianxin Chang +5
Sequential recommendation is one of the most important tasks in recommender systems, which aims to recommend the next interacted item with historical behaviors as input. Traditiona…