Papers with Token-specific Label Smoothing approach

1 papers
Self-Evolution Learning for Discriminative Language Model Pretraining (2023.findings-acl)

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Challenge: Random masking does not consider the importance of the different words in the sentence meaning, e.g., entity-level masking requires expensive prior knowledge and generally does not use existing model weights.
Approach: They propose a token masking and learning method that uses a random masking strategy to learn the under-explored tokens.
Outcome: The proposed method improves linguistic knowledge learning and generalization on 10 tasks.

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