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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 141–150 of 1773 papers

TitleStatusHype
Masked Language Model ScoringCode1
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative FlowCode1
Context-Aware Monolingual Repair for Neural Machine TranslationCode1
The MuCoW Test Suite at WMT 2019: Automatically Harvested Multilingual Contrastive Word Sense Disambiguation Test Sets for Machine TranslationCode1
Structure-Invariant Testing for Machine TranslationCode1
Effective Adversarial Regularization for Neural Machine TranslationCode1
Neural Machine Translating from Natural Language to SPARQLCode1
Domain Adaptation of Neural Machine Translation by Lexicon InductionCode1
When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical CohesionCode1
What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP ModelsCode1
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