Translation Task
Machine translation (MT) research focuses on automatically translating text between languages, aiming to improve accuracy, efficiency, and fluency. Current efforts concentrate on leveraging large language models (LLMs) and transformer architectures, often incorporating techniques like multilingual training, transfer learning, and data augmentation to address challenges posed by low-resource languages and diverse text types. These advancements are significantly impacting fields like cross-lingual communication, information access, and software localization, driving improvements in both the quality and accessibility of MT systems.
Papers
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