Paper: arxiv.org/abs/2407.12126
Machine translation is indispensable in healthcare for enabling the global dissemination of medical knowledge across languages. However, complex medical terminology poses unique challenges to achieving adequate translation quality and
accuracy. This study introduces a novel ”LLMs-in-the-loop” approach to develop
supervised neural machine translation models optimized specifically for medical
texts. While large language models (LLMs) have demonstrated… See the full description on the dataset page:
https://huggingface.co/datasets/aimped/medical-translation-test-set.
