Efficient Structured Prediction with Transformer Encoders
Finetuning is a useful method for adapting Transformer-based text encoders to new tasks but can be computationally expensive for structured prediction tasks that require tuning at the token level. Furthermore, finetuning is inherently inefficient in updating all base model parameters, which prevent...
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Format: | Article |
Language: | English |
Published: |
Linköping University Electronic Press
2024-12-01
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Series: | Northern European Journal of Language Technology |
Online Access: | https://nejlt.ep.liu.se/article/view/4932 |
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