2 papers
cs.LG2026
Robust Contrastive Graph Clustering with Adaptive Local-Global Integration
Lei Zhang, Fubo Sun, Haipeng Yang +2
Graph clustering is essential in graph analysis for revealing structural patterns and node communities. Despite recent advances in self-supervised contrastive learning that have im…
cs.IR2026
GCIB: Graph Contrastive Information Bottleneck for Multi-Behavior Recommendation
Likang Wu, Zihao Chen, Jianxin Zhang +4
With the rapid emergence of multi-behavior learning in recommender systems, leveraging auxiliary user behaviors has proven effective for mitigating target-behavior data sparsity. Y…