Papers by Guangfeng Yan

1 papers
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification (2020.acl-main)

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Challenge: Existing methods for unknown intent detection are limited by prior knowledge of class labels.
Approach: They propose to use a Gaussian mixture model to model utterance embeddings with a distribution and inject dynamic class semantic information into Gausssian means.
Outcome: The proposed model performs well on three real task-oriented dialogue datasets in two languages.

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