Papers with WMT’21 multilingual translation task

1 papers
Building Multilingual Machine Translation Systems That Serve Arbitrary XY Translations (2022.naacl-main)

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Challenge: Multilingual Neural Machine Translation (MNMT) systems are often limited to many-to-one directions and suffer from poor performance in one-to one directions.
Approach: They propose to build multilingual machine translation systems that serve arbitrary X-Y directions while leveraging multilinguality with a two-stage training strategy of pretraining and finetuning.
Outcome: The proposed system outperforms baseline bilingual models and pivot translation models in most directions without the need for architecture change or extra data collection.

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