6 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.IR2022★ 6 cited
CROLoss: Towards a Customizable Loss for Retrieval Models in Recommender Systems
Yongxiang Tang, Wentao Bai, Guilin Li +2
In large-scale recommender systems, retrieving top N relevant candidates accurately with resource constrain is crucial. To evaluate the performance of such retrieval models, Recall…
cs.IR2022★ 1 cited
Soft Retargeting Network for Click Through Rate Prediction
Xiaochen Li, Xin Song, Pengjia Yuan +2
The study of user interest models has received a great deal of attention in click through rate (CTR) prediction recently. These models aim at capturing user interest from different…
cs.IR2022
Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction
Xiaochen Li, Rui Zhong, Jian Liang +2
Rich user behavior information is of great importance for capturing and understanding user interest in click-through rate (CTR) prediction. To improve the richness, collecting long…