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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 121–130 of 1773 papers

TitleStatusHype
Convergences and Divergences between Automatic Assessment and Human Evaluation: Insights from Comparing ChatGPT-Generated Translation and Neural Machine Translation—0
Predicting Human Translation Difficulty with Neural Machine Translation—0
An Empirical study of Unsupervised Neural Machine Translation: analyzing NMT output, model's behavior and sentences' contribution—0
Distinguishing Translations by Human, NMT, and ChatGPT: A Linguistic and Statistical Approach—0
Unraveling Key Factors of Knowledge Distillation—0
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning—0
Improving Neural Machine Translation by Multi-Knowledge Integration with Prompting—0
Simul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models—0
Relevance-guided Neural Machine Translation—0
Reducing Gender Bias in Machine Translation through Counterfactual Data Generation—0
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