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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 631–640 of 1773 papers

TitleStatusHype
On the Effectiveness of Quasi Character-Level Models for Machine Translation—0
Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer—0
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
Digging Errors in NMT: Evaluating and Understanding Model Errors from Hypothesis Distribution—0
Modeling Multi-granularity Segmentation for Rare Words in Neural Machine Translation—0
Contrastive Word Embedding Learning for Neural Machine Translation—0
Modeling Future for Neural Machine Translation by Fusing Target Information—0
Towards Full Utilization on Mask Task for Distilling PLMs into NMT—0
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