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University of Rhode Island
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AdaptoNet recovers detection performance from below 12% to over 81% in the face of targeted cyber attacks, showcasing a revolutionary approach to resilience in power grid security.
Equivariant networks can now achieve superior performance across accuracy, efficiency, and speed, challenging the dominance of non-equivariant architectures.
Forget PEFT and KD, reprogramming distillation offers a surprisingly effective and robust way to adapt large medical foundation models to diverse downstream tasks.
