101 citations · 101 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Graph Augmentation for Recommendation
Qianru Zhang, Lianghao Xia, Xuheng Cai +3
Graph augmentation with contrastive learning has gained significant attention in the field of recommendation systems due to its ability to learn expressive user representations, ev…
cs.IR2023
How Expressive are Graph Neural Networks in Recommendation?
Xuheng Cai, Lianghao Xia, Xubin Ren +1
Graph Neural Networks (GNNs) have demonstrated superior performance on various graph learning tasks, including recommendation, where they leverage user-item collaborative filtering…
cs.IR2023★ 101 cited
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation
Xuheng Cai, Chao Huang, Lianghao Xia +1
Graph neural network (GNN) is a powerful learning approach for graph-based recommender systems. Recently, GNNs integrated with contrastive learning have shown superior performance…