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CKD: Contrastive Knowledge Distillation from A Sample-wise Perspective
April 23, 2024, 4:47 a.m. | Wencheng Zhu, Xin Zhou, Pengfei Zhu, Yu Wang, Qinghua Hu
cs.CV updates on arXiv.org arxiv.org
Abstract: In this paper, we present a simple yet effective contrastive knowledge distillation approach, which can be formulated as a sample-wise alignment problem with intra- and inter-sample constraints. Unlike traditional knowledge distillation methods that concentrate on maximizing feature similarities or preserving class-wise semantic correlations between teacher and student features, our method attempts to recover the "dark knowledge" by aligning sample-wise teacher and student logits. Specifically, our method first minimizes logit differences within the same sample by …
arxiv cs.cv distillation knowledge perspective sample type wise
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