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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 281–290 of 1773 papers

TitleStatusHype
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation—0
Examining Structure of Word Embeddings with PCA—0
Automatic Translation for Multiple NLP tasks: a Multi-task Approach to Machine-oriented NMT Adaptation—0
Addressing Asymmetry in Multilingual Neural Machine Translation with Fuzzy Task Clustering—0
Ancient-Modern Chinese Translation with a Large Training Dataset—0
A Comprehensive Evaluation of Neural SPARQL Query Generation from Natural Language Questions—0
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval—0
Construction of an Evaluation Corpus for Grammatical Error Correction for Learners of Japanese as a Second Language—0
Automatic Bilingual Phrase Dictionary Construction from GIZA++ Output—0
An Augmented Translation Technique for low Resource language pair: Sanskrit to Hindi translation—0
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