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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 871–880 of 1773 papers

TitleStatusHype
Evaluating the Performance of Back-translation for Low Resource English-Marathi Language Pair: CFILT-IITBombay @ LoResMT 2021—0
Learning How to Translate North Korean through South Korean—0
C-NMT: A Collaborative Inference Framework for Neural Machine Translation—0
A Simple and General Strategy for Referential Problem in Low-Resource Neural Machine Translation—0
LIUM's Contributions to the WMT2019 News Translation Task: Data and Systems for German-French Language Pairs—0
Document-level Neural Machine Translation with Document Embeddings—0
Learning Source Phrase Representations for Neural Machine Translation—0
Document-level Neural Machine Translation with Associated Memory Network—0
Learning to Discriminate Noises for Incorporating External Information in Neural Machine Translation—0
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation—0
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