101 citations · 185 across the 2 of their papers we have counts for
2 papers
cs.IR2023★ 84 cited
Graph Transformer for Recommendation
Chaoliu Li, Lianghao Xia, Xubin Ren +3
This paper presents a novel approach to representation learning in recommender systems by integrating generative self-supervised learning with graph transformer architecture. We hi…
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…