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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 941–950 of 1773 papers

TitleStatusHype
QCRI Machine Translation Systems for IWSLT 16—0
QCRI’s Machine Translation Systems for IWSLT’16—0
QE-EBM: Using Quality Estimators as Energy Loss for Machine Translation—0
Quality-Aware Decoding for Neural Machine Translation—0
Quality-Aware Decoding: Unifying Quality Estimation and Decoding—0
Quality-Aware Translation Models: Efficient Generation and Quality Estimation in a Single Model—0
Quality Estimation based Feedback Training for Improving Pronoun Translation—0
Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource Translation—0
Quantitative Analysis of Post-Editing Effort Indicators for NMT—0
Quantity vs. Quality of Monolingual Source Data in Automatic Text Translation: Can It Be Too Little If It Is Too Good?—0
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