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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

Showing 17011725 of 1773 papers

TitleStatusHype
OpenNMT: Open-Source Toolkit for Neural Machine TranslationCode0
Neural Machine Translation on Scarce-Resource Condition: A case-study on Persian-English0
Joint Prediction of Word Alignment with Alignment Types0
Fast Domain Adaptation for Neural Machine Translation0
Domain specialization: a post-training domain adaptation for Neural Machine Translation0
Neural Machine Translation from Simplified Translations0
Domain Control for Neural Machine Translation0
Boosting Neural Machine Translation0
How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation PairsCode0
Neural Machine Translation by Minimising the Bayes-risk with Respect to Syntactic Translation Lattices0
QCRI’s Machine Translation Systems for IWSLT’160
Adaptation and Combination of NMT Systems: The KIT Translation Systems for IWSLT 20160
Multilingual Disfluency Removal using NMT0
Factored Neural Machine Translation Architectures0
FBK’s Neural Machine Translation Systems for IWSLT 20160
UFAL Submissions to the IWSLT 2016 MT Track0
Kyoto-NMT: a Neural Machine Translation implementation in ChainerCode0
Topic-Informed Neural Machine Translation0
Ensemble Learning for Multi-Source Neural Machine Translation0
What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation0
A Character-Aware Encoder for Neural Machine Translation0
Residual Stacking of RNNs for Neural Machine Translation0
Faster and Lighter Phrase-based Machine Translation Baseline0
Character-based Decoding in Tree-to-Sequence Attention-based Neural Machine Translation0
A study of attention-based neural machine translation model on Indian languages0
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