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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 111–120 of 1773 papers

TitleStatusHype
Large Language Models "Ad Referendum": How Good Are They at Machine Translation in the Legal Domain?—0
Promoting Target Data in Context-aware Neural Machine Translation—0
Neural Machine Translation for Malayalam Paraphrase Generation—0
Salute the Classic: Revisiting Challenges of Machine Translation in the Age of Large Language ModelsCode0
Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation—0
Machine Translation Models are Zero-Shot Detectors of Translation DirectionCode0
An approach for mistranslation removal from popular dataset for Indic MT Task—0
POMP: Probability-driven Meta-graph Prompter for LLMs in Low-resource Unsupervised Neural Machine Translation—0
End to end Hindi to English speech conversion using Bark, mBART and a finetuned XLSR Wav2Vec2—0
Towards Boosting Many-to-Many Multilingual Machine Translation with Large Language ModelsCode0
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