Papers by Spencer Koehler

1 papers
PCMID: Multi-Intent Detection through Supervised Prototypical Contrastive Learning (2023.findings-emnlp)

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Challenge: Existing approaches to intent detection assume that each utterance represents only a single intent.
Approach: They propose a framework for intent detection that can learn multiple representations of a given user utterance under the context of different intent labels in an optimized semantic space.
Outcome: The proposed framework achieves state-of-the-art on multiple public benchmark datasets and a private real-world dataset for the multi-intent detection task.

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