Kdenxe.zip -

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Traditional KD methods minimize the Kullback-Leibler (KL) divergence between the softened probability distributions of the teacher and student. While effective, KL divergence treats class probabilities in isolation, often failing to capture the complex geometric relationships between classes in the logit space. Furthermore, standard KD suffers from gradient vanishing issues when the teacher and student capacities differ significantly. To give you a , please clarify: :

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