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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 91100 of 1773 papers

TitleStatusHype
Towards a Better Integration of Fuzzy Matches in Neural Machine Translation through Data AugmentationCode1
N-Bref : A High-fidelity Decompiler Exploiting Programming StructuresCode1
Learning Light-Weight Translation Models from Deep TransformerCode1
An Unsupervised method for OCR Post-Correction and Spelling Normalisation for FinnishCode1
PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated ContentsCode1
Emergent Communication Pretraining for Few-Shot Machine TranslationCode1
The MUCOW word sense disambiguation test suite at WMT 2020Code1
Analyzing the Source and Target Contributions to Predictions in Neural Machine TranslationCode1
Human-Paraphrased References Improve Neural Machine TranslationCode1
On Long-Tailed Phenomena in Neural Machine TranslationCode1
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