10 citations · 45 across the 20 of their papers we have counts for
4 papers · 1 filter
Pretrained Language Model based Web Search Ranking: From Relevance to Satisfaction
Canjia Li, Xiaoyang Wang, Dongdong Li +6
Search engine plays a crucial role in satisfying users' diverse information needs. Recently, Pretrained Language Models (PLMs) based text ranking models have achieved huge success…
Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation
Shengyu Zhang, Lingxiao Yang, Dong Yao +5
Effectively representing users lie at the core of modern recommender systems. Since users' interests naturally exhibit multiple aspects, it is of increasing interest to develop mul…
MIC: Model-agnostic Integrated Cross-channel Recommenders
Yujie Lu, Ping Nie, Shengyu Zhang +4
Semantically connecting users and items is a fundamental problem for the matching stage of an industrial recommender system. Recent advances in this topic are based on multi-channe…
Future-Aware Diverse Trends Framework for Recommendation
Yujie Lu, Shengyu Zhang, Yingxuan Huang +4
In recommender systems, modeling user-item behaviors is essential for user representation learning. Existing sequential recommenders consider the sequential correlations between hi…