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An initial six-client federation of real citation networks and synthetic structural proxies showed that degree divergence remained associated with harm, although more weakly, and survived removal of domain contrast, and expanding to twenty clients showed that degree divergence remained associated with harm, although more weakly, and survived removal of domain contrast.
Federated GNNs can converge numerically but still fail to learn meaningful relational structure due to destructive interference during aggregation of heterogeneous client updates.