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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 301–310 of 1773 papers

TitleStatusHype
FeatureBART: Feature Based Sequence-to-Sequence Pre-Training for Low-Resource NMT—0
CoDoNMT: Modeling Cohesion Devices for Document-Level Neural Machine TranslationCode0
Blur the Linguistic Boundary: Interpreting Chinese Buddhist Sutra in English via Neural Machine Translation—0
The first neural machine translation system for the Erzya languageCode1
Toward Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models—0
Revisiting Neural Scaling Laws in Language and Vision—0
Knowledge Based Template Machine Translation In Low-Resource Setting—0
On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine TranslationCode0
Multilingual Bidirectional Unsupervised Translation Through Multilingual Finetuning and Back-TranslationCode0
Current Shortcomings of Machine Translation in Spanish and Bulgarian Vis-à-vis English—0
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