A Chinese Few-Shot Text Classification Method Utilizing Improved Prompt Learning and Unlabeled Data
Insufficiently labeled samples and low-generalization performance have become significant natural language processing problems, drawing significant concern for few-shot text classification (FSTC). Advances in prompt learning have significantly improved the performance of FSTC. However, prompt learni...
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| Hlavní autoři: | , , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
MDPI AG
2023-03-01
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| Edice: | Applied Sciences |
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| On-line přístup: | https://www.mdpi.com/2076-3417/13/5/3334 |
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