66 citations · 271 across the 20 of their papers we have counts for
6 papers · 1 filter
General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout
An Zhang, Wenchang Ma, Pengbo Wei +2
Graph neural networks (GNNs) have shown impressive performance in recommender systems, particularly in collaborative filtering (CF). The key lies in aggregating neighborhood inform…
Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss
An Zhang, Leheng Sheng, Zhibo Cai +2
Contrastive Learning (CL) has achieved impressive performance in self-supervised learning tasks, showing superior generalization ability. Inspired by the success, adopting CL into…
Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation
Chengpeng Li, Zhengyi Yang, Jizhi Zhang +4
Reinforcement learning (RL) has been widely applied in recommendation systems due to its potential in optimizing the long-term engagement of users. From the perspective of RL, reco…
Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation
Wei Ji, Xiangyan Liu, An Zhang +3
Multi-modal recommendation systems, which integrate diverse types of information, have gained widespread attention in recent years. However, compared to traditional collaborative f…
Context-aware Event Forecasting via Graph Disentanglement
Yunshan Ma, Chenchen Ye, Zijian Wu +3
Event forecasting has been a demanding and challenging task throughout the entire human history. It plays a pivotal role in crisis alarming and disaster prevention in various aspec…
Invariant Collaborative Filtering to Popularity Distribution Shift
An Zhang, Jingnan Zheng, Xiang Wang +2
Collaborative Filtering (CF) models, despite their great success, suffer from severe performance drops due to popularity distribution shifts, where these changes are ubiquitous and…