Large Language Models Beat Commercial MT Models for Arabic Dialects, Research Finds
New research shows that large language models are better translators of Arabic dialects than commercial machine translation systems but remain far from perfect.
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New research shows that large language models are better translators of Arabic dialects than commercial machine translation systems but remain far from perfect.
Large language models offer new applications for traditional translation memory technologies. There’s a case for TMs to remain an important part of translation workflows.
“Wonderful”! A member of Germany’s parliament creates a watershed moment for the acceptance of consumer-grade translation AI.
A study introduces an approach to streamline translation between related languages, with the goal of enhancing trade efficiency and strengthening social connections, particularly in regions with related languages.
Amid a deluge of research into speech translation, many of the world’s leading technology companies are teaming up with academia to accelerate progress in this challenging field of language AI.
Brown University researchers reveal an issue with AI safety mechanisms in large language models involving low-resource languages.
A study demonstrates the ability of large language models to remove noise from datasets and underscores their potential for data cleaning.
Carnegie Mellon University researchers explore LLM effectiveness across 204 languages revealing their output limitations for low-resource languages.
Interest in automating machine translation quality estimation increases with the prevalence of large language models, but still has some way to go to be deployed at scale.
At SlatorCon Zurich, Dr. Sheila Castilho emphasizes the significance of contextual evaluation in assessing large language models and the need for a more rigorous evaluation approach.
Panelists from ServiceNow, LanguageWire, Busch Vacuum Solutions weighed the risks and opportunities of employing large language models in practical enterprise localization workflows.
Intento secures additional backers for its generative AI platform in USD 8m Series A funding as investors pick company in “crowded” translation and localization space.
The Slator Pro Guide: Translation AI is a vital and concise guide to applying large language models (LLMs) in translation workflows, featuring 10 practical use cases.
Monash University researchers show that large language models can do real-time machine translation and propose new ways for model fine-tuning.
Enterprise generative AI company Writer, Inc. completes a Series B round of funding, securing USD 100m from seven investors; plans to expand industry-specific LLMs.
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