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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 161–170 of 1773 papers

TitleStatusHype
Gender-specific Machine Translation with Large Language Models—0
Epi-Curriculum: Episodic Curriculum Learning for Low-Resource Domain Adaptation in Neural Machine Translation—0
Impact of Visual Context on Noisy Multimodal NMT: An Empirical Study for English to Indian LanguagesCode0
A Classification-Guided Approach for Adversarial Attacks against Neural Machine TranslationCode0
CLIPTrans: Transferring Visual Knowledge with Pre-trained Models for Multimodal Machine TranslationCode1
An Empirical Study of Consistency Regularization for End-to-End Speech-to-Text TranslationCode0
Ngambay-French Neural Machine Translation (sba-Fr)Code0
An Effective Method using Phrase Mechanism in Neural Machine TranslationCode0
Is context all you need? Scaling Neural Sign Language Translation to Large Domains of Discourse—0
Fast Training of NMT Model with Data Sorting—0
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