Papers with Document-level Neural Machine Translations

1 papers
Enhancing Context Modeling with a Query-Guided Capsule Network for Document-level Translation (D19-1)

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Challenge: Context modeling is essential to generate coherent and consistent translation for document-level Neural Machine Translations.
Approach: They propose a query-guided capsule network to cluster context information into different perspectives from which the target translation may concern.
Outcome: The proposed model outperforms baseline models on multiple datasets of different domains.

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