arXiv Machine Learning August 18, 2026 By Yuhang Song, Naima Abrar Shami, Romaric Duvignau, Vasiliki Kalavri

Not All Neighbors Matter: Understanding the Impact of Graph Sparsification on GNN Pipelines

Read the original on arXiv Machine Learning →

arXiv:2603. 06952v2 Announce Type: replace Abstract: As graphs scale to billions of nodes and edges, graph Machine Learning workloads are constrained by the cost of multi-hop traversals over exponentially growing neighborhoods.

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OgBench: A Framework for Evaluating Graph Neural Networks on Omics Data

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CoRe-GNN: Multilevel Message passing on Coarsened graphs

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