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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 191–200 of 1773 papers

TitleStatusHype
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
CODET: A Benchmark for Contrastive Dialectal Evaluation of Machine Translation—0
Bridging the Domain Gaps in Context Representations for k-Nearest Neighbor Neural Machine TranslationCode1
On the Copying Problem of Unsupervised NMT: A Training Schedule with a Language Discriminator LossCode0
Gender Lost In Translation: How Bridging The Gap Between Languages Affects Gender Bias in Zero-Shot Multilingual TranslationCode0
Songs Across Borders: Singable and Controllable Neural Lyric TranslationCode1
Do GPTs Produce Less Literal Translations?Code0
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