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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 41–50 of 1773 papers

TitleStatusHype
Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Ordering—0
NMT-Obfuscator Attack: Ignore a sentence in translation with only one wordCode0
Deceiving Question-Answering Models: A Hybrid Word-Level Adversarial ApproachCode0
On Creating an English-Thai Code-switched Machine Translation in Medical DomainCode0
Quantity vs. Quality of Monolingual Source Data in Automatic Text Translation: Can It Be Too Little If It Is Too Good?—0
Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset RepositoryCode0
QE-EBM: Using Quality Estimators as Energy Loss for Machine Translation—0
NusaMT-7B: Machine Translation for Low-Resource Indonesian Languages with Large Language Models—0
Optimizing the Training Schedule of Multilingual NMT using Reinforcement LearningCode0
On Instruction-Finetuning Neural Machine Translation Models—0
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