31 citations · 78 across the 15 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.IR2022★ 1 cited
Reinforced Path Reasoning for Counterfactual Explainable Recommendation
Xiangmeng Wang, Qian Li, Dianer Yu +1
Counterfactual explanations interpret the recommendation mechanism via exploring how minimal alterations on items or users affect the recommendation decisions. Existing counterfact…
cs.LG2022★ 31 cited
Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning
Haoran Yang, Hongxu Chen, Sixiao Zhang +4
Graph contrastive learning has emerged as a powerful tool for unsupervised graph representation learning. The key to the success of graph contrastive learning is to acquire high-qu…
cs.IR2022★ 12 cited
Causal Disentanglement for Semantics-Aware Intent Learning in Recommendation
Xiangmeng Wang, Qian Li, Dianer Yu +3
Traditional recommendation models trained on observational interaction data have generated large impacts in a wide range of applications, it faces bias problems that cover users' t…