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Standard knowledge distillation can harm model performance, but new reliability-aware methods can boost summarization accuracy by over 50 times the improvement of traditional approaches.
Forget individual data points? Child's play. This work lets you surgically remove entire *classes* of data from CNNs without catastrophic forgetting.
