Papers by Kazunori Imoto
VE-KD: Vocabulary-Expansion Knowledge-Distillation for Training Smaller Domain-Specific Language Models (2024.findings-emnlp)
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| Challenge: | VE-KD is a method that balances knowledge distillation and vocabulary expansion with the aim of training efficient domain-specific language models. |
| Approach: | They propose a method that balances knowledge distillation and vocabulary expansion with the aim of training efficient domain-specific language models. |
| Outcome: | VE-KD outperforms DistilBERT and Adapt-and-Distill in biomedical domain tasks . compared with other methods, it outperformed Distilbert and adapted-and distill . |