Papers with LGTM

1 papers
Tailoring Instructions to Student’s Learning Levels Boosts Knowledge Distillation (2023.acl-long)

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Challenge: Recent success of natural language processing (NLP) is driven by the adoption of large-scale pretrained language models.
Approach: They propose a method to determine the impact of distillation influence on student generalization ability by prioritizing samples likely to enhance the student's generalization abilities.
Outcome: The proposed method outperforms 10 common knowledge distillation baselines on 6 text classification tasks in the GLUE benchmark.

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