Papers with unified multilingual dialogue model

1 papers
MulZDG: Multilingual Code-Switching Framework for Zero-shot Dialogue Generation (2022.coling-1)

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Challenge: Existing zero-shot dialogue generation systems rely on large-scale pre-trained language models.
Approach: They propose a multilingual learning framework for zero-shot dialogue generation that can transfer knowledge from an English corpus to a non-English corpus with zero samples.
Outcome: The proposed framework can transfer knowledge from an English corpus to a non-English corpus with zero samples.

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