Papers by Xinzhong Sun

1 papers
A Transformer-based Threshold-Free Framework for Multi-Intent NLU (2022.coling-1)

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Challenge: Existing models for multi-intent natural language understanding mainly detect multiple intents on threshold settings.
Approach: They propose a transformer-based multi-intent NLU model with multi-task learning that exploits the information of the number of multiple intents in each utterance without additional manual annotations.
Outcome: The proposed model achieves superior results on two public multi-intent datasets.

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