arXiv Machine Learning June 10, 2026 By Lianze Shan, Ningchong Wang, Jitao Zhao, Di Jin, Dongxiao He

Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing

Read the original on arXiv Machine Learning →

arXiv:2606. 10284v1 Announce Type: new Abstract: Graph Contrastive Learning (GCL), which trains graph encoders by maximizing similarity between positive samples and minimizing it between negative ones, has emerged as a mainstream graph pre-training paradigm.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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