Papers with cross-task strong baselines

1 papers
TransPrompt: Towards an Automatic Transferable Prompting Framework for Few-shot Text Classification (2021.emnlp-main)

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Challenge: Recent studies show that prompts improve performance of large pre-trained language models for few-shot text classification.
Approach: They propose a prompt-based framework for few-shot learning that captures cross-task transferable knowledge and uses two de-biasing techniques to make it more task-agnostic and unbiased .
Outcome: The proposed framework outperforms strong baselines over multiple NLP tasks and datasets.

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