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Found 4 papers, 4 papers with code
ProtAugment: Intent Detection Meta-Learning through Unsupervised Diverse Paraphrasing
It relies on diverse paraphrasing: a conditional language model is first fine-tuned for paraphrasing, and diversity is later introduced at the decoding stage at each meta-learning episode.
ProtAugment: Unsupervised diverse short-texts paraphrasing for intent detection meta-learning
It relies on diverse paraphrasing: a conditional language model is first fine-tuned for paraphrasing, and diversity is later introduced at the decoding stage at each meta-learning episode.
A Neural Few-Shot Text Classification Reality Check
Additionally, some models used in Computer Vision are yet to be tested in NLP applications.
Few-shot Pseudo-Labeling for Intent Detection
This performance is achieved on multiple intent detection datasets, even in more challenging situations where the number of classes is large or when the dataset is highly imbalanced.
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