SPIN Unprocessed July 8, 2026 ai_technology research
Breaking Structural Isolation: Scalable Graph Clustering via Community-Aware Sampling and Structural Entropy
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arXiv:2607.05469v1 Announce Type: new Abstract: Unsupervised graph clustering is a fundamental technique for uncovering underlying semantic patterns in large-scale networks. Although Graph Contrastive Learning has demonstrated promising performance, existing methods often suffer from the "structural isolation" issue during mini-batch training, making it challenging to capture cohesive community structures that characterize the global topological distribution. To address these challenges, we prop
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