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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 341–350 of 1773 papers

TitleStatusHype
On Search Strategies for Document-Level Neural Machine Translation—0
Improving Long Context Document-Level Machine Translation—0
Extract and Attend: Improving Entity Translation in Neural Machine Translation—0
Leveraging Auxiliary Domain Parallel Data in Intermediate Task Fine-tuning for Low-resource TranslationCode0
Assessing the Importance of Frequency versus Compositionality for Subword-based Tokenization in NMTCode0
How Does Pretraining Improve Discourse-Aware Translation?—0
Translation-Enhanced Multilingual Text-to-Image Generation—0
Augmenting Large Language Model Translators via Translation Memories—0
Do GPTs Produce Less Literal Translations?Code0
On the Copying Problem of Unsupervised NMT: A Training Schedule with a Language Discriminator LossCode0
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