Here, we present the Long Range Graph Benchmark (LRGB) 1 with 5 graph learning datasets: PascalVOC-SP , COCO-SP , PCQM-Contact , Peptides-func and Peptides-struct that arguably require LRI reasoning to achieve strong performance in a given task. We benchmark both baseline GNNs and Graph Transformer networks to verify that the models which capture long-range dependencies perform significantly better on these tasks. Therefore, these datasets are suitable for benchmarking and exploration of MP-GNNs and Graph Transformer architectures that are intended to capture LRI.
2022: Vijay Prakash Dwivedi, Ladislav Rampášek, Mikhail Galkin, Alipanah Parviz, Guy Wolf, A. Luu, D. Beaini
Ranked #1 on Node Classification on PascalVOC-SP
https://arxiv.org/pdf/2206.08164v1.pdf
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