Papers by Tae-Yoon Kim

1 papers
SUMBT: Slot-Utterance Matching for Universal and Scalable Belief Tracking (P19-1)

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Challenge: Existing methods to model domain- and slot-dependent belief trackers have difficulty adding new slot-values, resulting in lack of flexibility of domain ontology configurations.
Approach: They propose a model that captures relationships between domain-slot-types and slot-values appearing in utterances through attention mechanisms based on contextual semantic vectors.
Outcome: The proposed model improves performance on two dialog corpora and achieves state-of-the-art accuracy.

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