Papers with text augmentation technique

1 papers
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems (2021.emnlp-main)

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Challenge: Large-scale pre-trained language models have shown promising results for few-shot learning in task-oriented dialog (ToD) systems.
Approach: They propose a self-training approach that iteratively labels the most confident unlabeled data to train a stronger Student model.
Outcome: The proposed approach improves state-of-the-art pre-trained models in few-shot learning scenarios for task-oriented dialog (ToD) systems when only a small number of labeled data are available.

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