Papers with discriminative user utterance representation learning

1 papers
CoCoID: Learning Contrastive Representations and Compact Clusters for Semi-Supervised Intent Discovery (2022.emnlp-industry)

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Challenge: Existing approaches to intent discovery cluster novel intents with prior knowledge from intent-labeled data in a semi-supervised way.
Approach: They propose a semi-supervised intent discovery framework CoCoID with two components . they propose to discriminate user utterance representation learning and intra-cluster knowledge distillation .
Outcome: The proposed framework outperforms state-of-the-art intent discovery models by over 1.4 ACC and ARI points and 1.1 NMI points across four datasets.

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