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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 1151–1160 of 1773 papers

TitleStatusHype
Learning to Discriminate Noises for Incorporating External Information in Neural Machine Translation—0
Learning to Generate Word- and Phrase-Embeddings for Efficient Phrase-Based Neural Machine Translation—0
Learning to Multi-Task Learn for Better Neural Machine Translation—0
Learning to Refine Source Representations for Neural Machine Translation—0
Learning to Reuse Translations: Guiding Neural Machine Translation with Examples—0
Learning to Segment Inputs for NMT Favors Character-Level Processing—0
Leveraging Diverse Modeling Contexts with Collaborating Learning for Neural Machine Translation—0
Leveraging GPT-4 for Automatic Translation Post-Editing—0
Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation—0
Lexical Micro-adaptation for Neural Machine Translation—0
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