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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 521–530 of 1773 papers

TitleStatusHype
EMMeTT: Efficient Multimodal Machine Translation Training—0
Efforts Towards Developing a Tamang Nepali Machine Translation System—0
AR: Auto-Repair the Synthetic Data for Neural Machine Translation—0
Effort-Aware Neural Automatic Post-Editing—0
Efficient Unsupervised NMT for Related Languages with Cross-Lingual Language Models and Fidelity Objectives—0
Can the Variation of Model Weights be used as a Criterion for Self-Paced Multilingual NMT?—0
Efficient Transfer Learning for Quality Estimation with Bottleneck Adapter Layer—0
Efficient Technical Term Translation: A Knowledge Distillation Approach for Parenthetical Terminology Translation—0
Can Synthetic Translations Improve Bitext Quality?—0
A Pronoun Test Suite Evaluation of the English--German MT Systems at WMT 2018—0
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