Papers with Transformer-based machine translation model

1 papers
A Discriminative Neural Model for Cross-Lingual Word Alignment (D19-1)

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Challenge: a novel word alignment model for machine translation has been developed for a number of languages . explicit word-to-word alignments have largely been lost in neural MT systems .
Approach: They propose a discriminative word alignment model which integrates into a Transformer-based machine translation model.
Outcome: The proposed model performs better on Chinese and Arabic alignments than standard models.

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