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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 191–200 of 1773 papers

TitleStatusHype
Enhancing Entertainment Translation for Indian Languages using Adaptive Context, Style and LLMs—0
Exploiting Domain-Specific Parallel Data on Multilingual Language Models for Low-resource Language Translation—0
Advancing Explainability in Neural Machine Translation: Analytical Metrics for Attention and Alignment Consistency—0
An Analysis on Automated Metrics for Evaluating Japanese-English Chat Translation—0
Domain adapted machine translation: What does catastrophic forgetting forget and why?—0
Reconsidering SMT Over NMT for Closely Related Languages: A Case Study of Persian-Hindi Pair—0
Understanding and Analyzing Model Robustness and Knowledge-Transfer in Multilingual Neural Machine Translation using TX-Ray—0
ParMod: A Parallel and Modular Framework for Learning Non-Markovian Tasks—0
A Comparative Study of LLMs, NMT Models, and Their Combination in Persian-English Idiom TranslationCode0
Shiksha: A Technical Domain focused Translation Dataset and Model for Indian Languages—0
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