Papers with zero-shot intent classification

2 papers
Exploring Zero and Few-shot Techniques for Intent Classification (2023.acl-industry)

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Challenge: Intent classification is the primary natural language understanding task for a virtual agent or a chatbot.
Approach: They propose four different approaches to zero-shot intent classification with low-resource constraints . they use domain adaptation, data augmentation, and parametric fine-tuning to achieve this .
Outcome: The proposed approaches perform well in low-resource settings for zero/few-shot intent classification . the proposed methods remove or substantially reduce the work to provide intent-utterances .
Reconstructing Capsule Networks for Zero-shot Intent Classification (D19-1)

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Challenge: Existing methods for intent classification are limited due to fast-emerging intents . a recent study shows that existing methods are not effective in recognizing unseen intents.
Approach: They propose to reconstruct capsule networks for zero-shot intent classification by using latent information from labeled utterances.
Outcome: The proposed method outperforms existing methods on two task-oriented dialogue datasets in different languages.

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