173 citations · 338 across the 11 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.IR2023★ 1 cited
GraphPro: Graph Pre-training and Prompt Learning for Recommendation
Yuhao Yang, Lianghao Xia, Da Luo +2
GNN-based recommenders have excelled in modeling intricate user-item interactions through multi-hop message passing. However, existing methods often overlook the dynamic nature of…
cs.IR2023★ 173 cited
Debiased Contrastive Learning for Sequential Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia +3
Current sequential recommender systems are proposed to tackle the dynamic user preference learning with various neural techniques, such as Transformer and Graph Neural Networks (GN…
cs.IR2023★ 125 cited
Automated Self-Supervised Learning for Recommendation
Lianghao Xia, Chao Huang, Chunzhen Huang +3
Graph neural networks (GNNs) have emerged as the state-of-the-art paradigm for collaborative filtering (CF). To improve the representation quality over limited labeled data, contra…