9 citations · 11 across the 5 of their papers we have counts for
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cs.IR2025
MUSE: A Simple Yet Effective Multimodal Search-Based Framework for Lifelong User Interest Modeling
Bin Wu, Feifan Yang, Zhangming Chan +8
Lifelong user interest modeling is crucial for industrial recommender systems, yet existing approaches rely predominantly on ID-based features, suffering from poor generalization o…
cs.IR2024★ 2 cited
Language-Model Prior Overcomes Cold-Start Items
Shiyu Wang, Hao Ding, Yupeng Gu +3
The growth of recommender systems (RecSys) is driven by digitization and the need for personalized content in areas such as e-commerce and video streaming. The content in these sys…
cs.IR2022
Everyone's Preference Changes Differently: Weighted Multi-Interest Retrieval Model
Hui Shi, Yupeng Gu, Yitong Zhou +3
User embeddings (vectorized representations of a user) are essential in recommendation systems. Numerous approaches have been proposed to construct a representation for the user in…