Wilfried Logerais
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View article: ProtAugment: Unsupervised diverse short-texts paraphrasing for intent detection meta-learning
ProtAugment: Unsupervised diverse short-texts paraphrasing for intent detection meta-learning Open
Recent research considers few-shot intent detection as a meta-learning problem: the model is learning to learn from a consecutive set of small tasks named episodes. In this work, we propose ProtAugment, a meta-learning algorithm for short …
View article: A Neural Few-Shot Text Classification Reality Check
A Neural Few-Shot Text Classification Reality Check Open
Modern classification models tend to struggle when the amount of annotated data is scarce. To overcome this issue, several neural few-shot classification models have emerged, yielding significant progress over time, both in Computer Vision…
View article: ProtAugment: Intent Detection Meta-Learning through Unsupervised Diverse Paraphrasing
ProtAugment: Intent Detection Meta-Learning through Unsupervised Diverse Paraphrasing Open
International audience
View article: Few-shot Pseudo-Labeling for Intent Detection
Few-shot Pseudo-Labeling for Intent Detection Open
International audience