2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.IR2022
Contrastive Information Transfer for Pre-Ranking Systems
Yue Cao, XiaoJiang Zhou, Peihao Huang +3
Real-word search and recommender systems usually adopt a multi-stage ranking architecture, including matching, pre-ranking, ranking, and re-ranking. Previous works mainly focus on…
cs.IR2022
AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System
Xiang Li, Xiaojiang Zhou, Yao Xiao +4
Industrial search and recommendation systems mostly follow the classic multi-stage information retrieval paradigm: matching, pre-ranking, ranking, and re-ranking stages. To account…
cs.IR2022★ 2 cited
Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction
Yue Cao, XiaoJiang Zhou, Jiaqi Feng +4
Rich user behavior data has been proven to be of great value for Click-Through Rate (CTR) prediction applications, especially in industrial recommender, search, or advertising syst…