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Jul 2026

DiffGCC: diffusion-enhanced global–local graph contrastive clustering

DiffGCC is a generative graph contrastive clustering framework that couples global–local feature encoding with a latent-space diffusion denoising mechanism and substantially outperforms existing methods across ACC, NMI, ARI, and F1, with particularly strong gains on denser, noisier product graphs.

Lun Liu, Chengyun Song · 0 citations