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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 1521–1530 of 1773 papers

TitleStatusHype
TransIns: Document Translation with Markup ReinsertionCode0
TopicVD: A Topic-Based Dataset of Video-Guided Multimodal Machine Translation for DocumentariesCode0
Multi-Class Grammatical Error Detection for Correction: A Tale of Two SystemsCode0
Multi-Domain Adaptation in Neural Machine Translation Through Multidimensional TaggingCode0
Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine TranslationCode0
Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel DataCode0
Multi-Domain Neural Machine Translation with Word-Level Domain Context DiscriminationCode0
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain MixingCode0
Otem&Utem: Over- and Under-Translation Evaluation Metric for NMTCode0
Translate, then Parse! A strong baseline for Cross-Lingual AMR ParsingCode0
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