3 papers
cs.IR2025
Stratified Expert Cloning for Retention-Aware Recommendation at Scale
Chengzhi Lin, Annan Xie, Shuchang Liu +3
User retention is critical in large-scale recommender systems, significantly influencing online platforms' long-term success. Existing methods typically focus on short-term engagem…
cs.LG2025
Conditional Quantile Estimation for Uncertain Watch Time in Short-Video Recommendation
Chengzhi Lin, Shuchang Liu, Chuyuan Wang +1
Accurately predicting watch time is crucial for optimizing recommendations and user experience in short video platforms. However, existing methods that estimate a single average wa…
cs.IR2025
AlignPxtr: Aligning Predicted Behavior Distributions for Bias-Free Video Recommendations
Chengzhi Lin, Chuyuan Wang, Annan Xie +5
In video recommendation systems, user behaviors such as watch time, likes, and follows are commonly used to infer user interest. However, these behaviors are influenced by various…