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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Bibliografische Detailangaben

Hauptverfasser:	Tingkai Hu, Zuqin Chen, Jike Ge, Zhaoxu Yang, Jichao Xu
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2023-03-01
Schriftenreihe:	Applied Sciences
Schlagworte:	Chinese few-shot text classification prompt learning unlabeled data pre-trained language model
Online-Zugang:	https://www.mdpi.com/2076-3417/13/5/3334
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