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From Phase Transition to Systemic Failure: A Decoupled Analytics Framework for GNN Robustness

arXiv:2609.31656v1 Announce Type: new Abstract: Data quality is a major bottleneck for the reliable deployment of graph neural networks (GNNs) in real-world graph mining tasks. Among various sources of degradation, label noise and feature distribution shift (hereafter referred to as distribution sh…

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  1. 2026-09-29 04:00 · arXiv cs.LG
    From Phase Transition to Systemic Failure: A Decoupled Analytics Framework for GNN Robustness

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