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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 21–30 of 1773 papers

TitleStatusHype
Extend Adversarial Policy Against Neural Machine Translation via Unknown Token—0
Proverbs Run in Pairs: Evaluating Proverb Translation Capability of Large Language Model—0
AFRIDOC-MT: Document-level MT Corpus for African LanguagesCode0
Bridging Dialects: Translating Standard Bangla to Regional Variants Using Neural Models—0
Quality Estimation based Feedback Training for Improving Pronoun Translation—0
Sinhala Transliteration: A Comparative Analysis Between Rule-based and Seq2Seq ApproachesCode0
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
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