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TransPrompt: Towards an Automatic Transferable Prompting Framework for Few-shot Text Classification

Chengyu Wang, Jianing Wang, Minghui Qiu, Jun Huang, Ming Gao
2021 Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing   unpublished
Based on continuous prompt embeddings, we propose TransPrompt, a transferable prompting framework for few-shot learning across similar tasks.  ...  Recent studies have shown that prompts improve the performance of large pre-trained language models for few-shot text classification.  ...  In this paper, we present TransPrompt, a prompting framework that allows PLMs to capture crosstask transferable knowledge for few-shot text classification, with the high-level architecture shown in Figure  ... 
doi:10.18653/v1/2021.emnlp-main.221 fatcat:k5s6pgzrkrfijfsg3va7z5phsm