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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 781–790 of 1773 papers

TitleStatusHype
Inference-only sub-character decomposition improves translation of unseen logographic characters—0
Information-Propogation-Enhanced Neural Machine Translation by Relation Model—0
Implicit Distortion and Fertility Models for Attention-based Encoder-Decoder NMT Model—0
Insights from Gathering MT Productivity Metrics at Scale—0
Implications of Multi-Word Expressions on English to Bharti Braille Machine Translation—0
Integrating Multi-Head Convolutional Encoders with Cross-Attention for Improved SPARQL Query Translation—0
Corpora for Document-Level Neural Machine Translation—0
AutoLoss: Learning Discrete Schedule for Alternate Optimization—0
Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages—0
An Analysis on Automated Metrics for Evaluating Japanese-English Chat Translation—0
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