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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 851–860 of 1773 papers

TitleStatusHype
Language Model-Driven Unsupervised Neural Machine Translation—0
Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT—0
Language Modelling with NMT Query Translation for Amharic-Arabic Cross-Language Information Retrieval—0
Language Models are Good Translators—0
Language Portability Strategies for Open-domain Dialogue with Pre-trained Language Models from High to Low Resource Languages—0
Language Relatedness and Lexical Closeness can help Improve Multilingual NMT: IITBombay@MultiIndicNMT WAT2021—0
A User Study of the Incremental Learning in NMT—0
Large-scale Pretraining for Neural Machine Translation with Tens of Billions of Sentence Pairs—0
Latent Part-of-Speech Sequences for Neural Machine Translation—0
An Analysis of Source-Side Grammatical Errors in NMT—0
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