[ajb117]

Besides the the title being a bit exaggerated, it's been long-acknowledged in the GNN community that graph rewiring often helps learning; see [1, 2] for example. Also, at first skim, I'm surprised there's no discussion on oversmoothing/oversquashing in this paper. It seems like what they're calling "overfitting" on the graph structure could be interpreted as the GNN's node representations saturating/starving because of poor graph topology.

[1] - https://arxiv.org/abs/2111.14522 [2] - https://arxiv.org/abs/2210.02997