Improving Machine Translation Formality with Large Language Models

Preserving formal style in neural machine translation (NMT) is essential, yet often overlooked as an optimization objective of the training processes. This oversight can lead to translations that, though accurate, lack formal... | Find, read and cite all the research you need on Tech Science Press

Authors

Publication Details

Journal
Computers, materials & continua/Computers, materials & continua (Print)
Published
2024-12-13
DOI
https://doi.org/10.32604/cmc.2024.058248
Citations
3
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
1.04
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article

Improving Machine Translation Formality with Large Language Models

Fuxue Li, Murun Yang
3 citations
Computers, materials & continua/Computers, materials & continua (Print)
Natural Language Processing Techniques
1.04
article

Improving Machine Translation Formality with Large Language Models

Fuxue Li, Murun Yang
article en
3 citations

Abstract

Preserving formal style in neural machine translation (NMT) is essential, yet often overlooked as an optimization objective of the training processes. This oversight can lead to translations that, though accurate, lack formal... | Find, read and cite all the research you need on Tech Science Press

Computers, materials & continua/Computers, materials & continua (Print)Vol. 82(2)
Openalex Percentile: Top 18%
Natural Language Processing Techniques
1.04
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Improving Machine Translation Formality with Large Language Models — Fuxue Li, Murun Yang · Computers, materials & continua/Computers, materials & continua (Print) (2024) | TGRS Research Map | TGRS