NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise

Neural Information Processing Systems 

Consequently, label noise is common in real-world graph data, negatively impacting GNNs by propagating incorrect information during training. To address this issue, the study of Graph Neural Networks under Label Noise (GLN) has recently gained traction.

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