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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 341–350 of 1773 papers

TitleStatusHype
A Two-Stage Curriculum Training Framework for NMT—0
Content-Equivalent Translated Parallel News Corpus and Extension of Domain Adaptation for NMT—0
ContraCAT: Contrastive Coreference Analytical Templates for Machine Translation—0
Contrastive Learning for Context-aware Neural Machine TranslationUsing Coreference Information—0
Contrastive Learning for Context-aware Neural Machine Translation Using Coreference Information—0
Contrastive Token Learning with Similarity Decay for Repetition Suppression in Machine Translation—0
Contrastive Word Embedding Learning for Neural Machine Translation—0
Controlling Formality in Low-Resource NMT with Domain Adaptation and Re-Ranking: SLT-CDT-UoS at IWSLT2022—0
Controlling Japanese Honorifics in English-to-Japanese Neural Machine Translation—0
A Transformer-Based Multi-Source Automatic Post-Editing System—0
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