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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 951–960 of 1773 papers

TitleStatusHype
Fine-Grained Error Analysis on English-to-Japanese Machine Translation in the Medical Domain—0
Fine Grained Human Evaluation for English-to-Chinese Machine Translation: A Case Study on Scientific Text—0
Finetuning a Kalaallisut-English machine translation system using web-crawled data—0
First Experiments with Neural Translation of Informal to Formal Mathematics—0
Fix-Filter-Fix: Intuitively Connect Any Models for Effective Bug Fixing—0
Fixing exposure bias with imitation learning needs powerful oracles—0
FJWU Participation for the WMT21 Biomedical Translation Task—0
Flow-Adapter Architecture for Unsupervised Machine Translation—0
Forest-Based Neural Machine Translation—0
FrameNet Annotations Alignment using Attention-based Machine Translation—0
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