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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 1571–1580 of 1773 papers

TitleStatusHype
PhraseTransformer: An Incorporation of Local Context Information into Sequence-to-sequence Semantic ParsingCode0
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back-TranslationCode0
Sentence Alignment with Parallel Documents Facilitates Biomedical Machine TranslationCode0
Multiscale Collaborative Deep Models for Neural Machine TranslationCode0
Multi-Sentence Resampling: A Simple Approach to Alleviate Dataset Length Bias and Beam-Search DegradationCode0
Ensembling Factored Neural Machine Translation Models for Automatic Post-Editing and Quality EstimationCode0
Pluggable Neural Machine Translation Models via Memory-augmented AdaptersCode0
CoDoNMT: Modeling Cohesion Devices for Document-Level Neural Machine TranslationCode0
Improving Neural Machine Translation with Conditional Sequence Generative Adversarial NetsCode0
ViNMT: Neural Machine Translation ToolkitCode0
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