75 citations · 83 across the 4 of their papers we have counts for
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cs.IR2023★ 2 cited
GEMRec: Towards Generative Model Recommendation
Yuanhe Guo, Haoming Liu, Hongyi Wen
Recommender Systems are built to retrieve relevant items to satisfy users' information needs. The candidate corpus usually consists of a finite set of items that are ready to be se…
cs.IR2021★ 3 cited
Evaluating Music Recommendations with Binary Feedback for Multiple Stakeholders
Sasha Stoikov, Hongyi Wen
High quality user feedback data is essential to training and evaluating a successful music recommendation system, particularly one that has to balance the needs of multiple stakeho…
cs.IR2021★ 3 cited
Correcting the User Feedback-Loop Bias for Recommendation Systems
Weishen Pan, Sen Cui, Hongyi Wen +3
Selection bias is prevalent in the data for training and evaluating recommendation systems with explicit feedback. For example, users tend to rate items they like. However, when ra…