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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 521–530 of 1773 papers

TitleStatusHype
Faithful Target Attribute Prediction in Neural Machine TranslationCode0
Non-Parametric Online Learning from Human Feedback for Neural Machine TranslationCode0
Learning Domain Specific Language Models for Automatic Speech Recognition through Machine Translation—0
Learning Kernel-Smoothed Machine Translation with Retrieved ExamplesCode1
Digging Errors in NMT: Evaluating and Understanding Model Errors from Hypothesis Distribution—0
Contrastive Word Embedding Learning for Neural Machine Translation—0
Modeling Future for Neural Machine Translation by Fusing Target Information—0
Modeling Multi-granularity Segmentation for Rare Words in Neural Machine Translation—0
Towards Full Utilization on Mask Task for Distilling PLMs into NMT—0
Translation Transformers Rediscover Inherent Data DomainsCode0
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