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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 791–800 of 1773 papers

TitleStatusHype
Contextual Text Embeddings for Twi—0
PENELOPIE: Enabling Open Information Extraction for the Greek Language through Machine TranslationCode0
Low-Resource Machine Translation Training Curriculum Fit for Low-Resource Languages—0
Repairing Pronouns in Translation with BERT-Based Post-Editing—0
Monolingual and Parallel Corpora for Kangri Low Resource LanguageCode0
Token-wise Curriculum Learning for Neural Machine Translation—0
Crowdsourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The Case of Fon Language—0
Unsupervised Transfer Learning in Multilingual Neural Machine Translation with Cross-Lingual Word Embeddings—0
Learning Feature Weights using Reward Modeling for Denoising Parallel Corpora—0
Self-Learning for Zero Shot Neural Machine Translation—0
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