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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 1491–1500 of 1773 papers

TitleStatusHype
Guiding attention in Sequence-to-sequence models for Dialogue Act predictionCode0
Incorporating Chinese Radicals Into Neural Machine Translation: Deeper Than Character LevelCode0
Salute the Classic: Revisiting Challenges of Machine Translation in the Age of Large Language ModelsCode0
Byte-based Multilingual NMT for Endangered LanguagesCode0
Domain Robustness in Neural Machine TranslationCode0
Handling Syntactic Divergence in Low-resource Machine TranslationCode0
Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine TranslationCode0
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource LanguagesCode0
On Using Distribution-Based Compositionality Assessment to Evaluate Compositional Generalisation in Machine TranslationCode0
Exploring Paracrawl for Document-level Neural Machine TranslationCode0
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