Papers with first-order derivatives

1 papers
Knowledge Distillation with Reptile Meta-Learning for Pretrained Language Model Compression (2022.coling-1)

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Challenge: Knowledge distillation (KD) can transfer knowledge from the original model into a compact model to achieve model compression.
Approach: They propose a knowledge distillation method with reptile meta-learning to facilitate the transfer of knowledge from the teacher to the student.
Outcome: Extensive experiments on the GLUE benchmark show the proposed method performs better than previous methods.

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