75 citations · 83 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Revisiting Adversarially Learned Injection Attacks Against Recommender Systems
Jiaxi Tang, Hongyi Wen, Ke Wang
Recommender systems play an important role in modern information and e-commerce applications. While increasing research is dedicated to improving the relevance and diversity of the…