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AlignGAE shatters the homophily bias barrier, achieving up to 18.7% better performance on heterophilous graphs compared to existing methods.
Observation-based corrections for distribution drift in temporal graph generation fail to significantly reduce error, with the best methods recovering only 5.7% of what an oracle achieves.
