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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 811–820 of 1773 papers

TitleStatusHype
Switching-Aligned-Words Data Augmentation for Neural Machine Translation—0
Translation Memory Guided Neural Machine Translation—0
Crowd-sourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The case of Fon Language—0
A Simple and General Strategy for Referential Problem in Low-Resource Neural Machine Translation—0
Learning to Use Future Information in Simultaneous TranslationCode0
Neural Machine Translation: A Review of Methods, Resources, and Tools—0
Revisiting Robust Neural Machine Translation: A Transformer Case Study—0
FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine TranslationCode0
Synthetic Source Language Augmentation for Colloquial Neural Machine Translation—0
Why Neural Machine Translation Prefers Empty Outputs—0
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