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Zhejiang University
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Static labels in medical AI are giving way to dynamic models that can simulate disease evolution and guide personalized interventions.
By generating synthetic gradients to bridge gaps between sparse benign updates, EnCAgg recovers more clean data in federated learning, even under dynamic model poisoning.