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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 926–950 of 1773 papers

TitleStatusHype
Who Evaluates the Evaluators? On Automatic Metrics for Assessing AI-based Offensive Code Generators—0
Why Find the Right One?—0
Why Neural Machine Translation Prefers Empty Outputs—0
Word Alignment in the Era of Deep Learning: A Tutorial—0
Word Rewarding for Adequate Neural Machine Translation—0
WT: Wipro AI Submissions to the WAT 2020—0
XMU Neural Machine Translation Online Service—0
xSIM++: An Improved Proxy to Bitext Mining Performance for Low-Resource Languages—0
YANMTT: Yet Another Neural Machine Translation Toolkit—0
Zero-Resource Neural Machine Translation with Multi-Agent Communication Game—0
Zero-Resource Neural Machine Translation with Monolingual Pivot Data—0
Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation—0
Zero-Shot Neural Machine Translation: Russian-Hindi @LoResMT 2020—0
Zero-Shot Neural Machine Translation with Self-Learning Cycle—0
Zero-shot translation among Indian languages—0
Zero-Shot Translation using Diffusion Models—0
Neural Machine Translation with Recurrent Highway Networks—0
FFR v1.1: Fon-French Neural Machine Translation—0
Filtering Back-Translated Data in Unsupervised Neural Machine Translation—0
Finding Sami Cognates with a Character-Based NMT Approach—0
Findings of the Fourth Workshop on Neural Generation and Translation—0
Findings of the WMT 2018 Shared Task on Automatic Post-Editing—0
Findings of the WMT 2020 Shared Task on Automatic Post-Editing—0
Finding the Right Recipe for Low Resource Domain Adaptation in Neural Machine Translation—0
Fine-Grained Attention Mechanism for Neural Machine Translation—0
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