This work presents an efficient yet effective online. Knowledge Distillation method via Collaborative Learn- ing, termed KDCL, which is able to consistently ...
Oct 27, 2022 · In this paper, we propose a novel framework that leverages both multi-teacher knowledge distillation and network quantization for learning low ...
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Mar 13, 2024 · A novel approach known as Collaborative Knowledge Distillation (CKD) is introduced, which is founded upon the concept of “Tailoring the Teaching to the ...
Mar 15, 2024 · The main idea of our FKT method is online knowledge distillation combined with entropy-based filter knowledge exchange. This method enables ...
Collaborative Distillation is a new knowledge distillation method (named Collaborative Distillation) for encoder-decoder based neural style transfer.
Sep 30, 2024 · The proposed framework enables efficient knowledge transfer among participating DNN nodes as needed, while enhancing their learning capabilities ...
Knowledge distillation (KD), as an efficient and effective model compression technique, has received considerable attention in deep learning.
Knowledge distillation (KD) is a technique used to transfer knowledge from a larger ''teacher'' model into a smaller ''student'' model.
This work presents an efficient yet effective online Knowledge Distillation method via Collaborative Learning, termed KDCL, which is able to consistently ...
In this paper, we present the discovery that a student model distilled from a few-shot prompted LLM can commonly generalize better than its teacher to unseen ...