86 citations · 289 across the 34 of their papers we have counts for
6 papers · 1 filter
QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback
Handong Ma, Jiawei Hou, Chenxu Zhu +6
Pseudo relevance feedback (PRF) automatically performs query expansion based on top-retrieved documents to better represent the user's information need so as to improve the search…
Cross-Batch Negative Sampling for Training Two-Tower Recommenders
Jinpeng Wang, Jieming Zhu, Xiuqiang He
The two-tower architecture has been widely applied for learning item and user representations, which is important for large-scale recommender systems. Many two-tower models are tra…
UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation
Kelong Mao, Jieming Zhu, Xi Xiao +3
With the recent success of graph convolutional networks (GCNs), they have been widely applied for recommendation, and achieved impressive performance gains. The core of GCNs lies i…
Why Do We Click: Visual Impression-aware News Recommendation
Jiahao Xun, Shengyu Zhang, Zhou Zhao +7
There is a soaring interest in the news recommendation research scenario due to the information overload. To accurately capture users' interests, we propose to model multi-modal fe…
SimpleX: A Simple and Strong Baseline for Collaborative Filtering
Kelong Mao, Jieming Zhu, Jinpeng Wang +4
Collaborative filtering (CF) is a widely studied research topic in recommender systems. The learning of a CF model generally depends on three major components, namely interaction e…
Modeling High-order Interactions across Multi-interests for Micro-video Recommendation
Dong Yao, Shengyu Zhang, Zhou Zhao +4
Personalized recommendation system has become pervasive in various video platform. Many effective methods have been proposed, but most of them didn't capture the user's multi-level…