MedMT5: An Open-Source Multilingual Text-to-Text LLM for the Medical Domain (2024.lrec-main)
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Iker García-Ferrero, Rodrigo Agerri, Aitziber Atutxa Salazar, Elena Cabrio, Iker de la Iglesia, Alberto Lavelli, Bernardo Magnini, Benjamin Molinet, Johana Ramirez-Romero, German Rigau, Jose Maria Villa-Gonzalez, Serena Villata, Andrea Zaninello
| Challenge: | Existing studies on large language models for medical applications have focused on a single language . medical mT5 outperforms both encoders and similar sized text-to-text models in English, French, and Italian benchmarks . |
| Approach: | They propose to train Medical mT5, the first open-source text-to-text multilingual model for the medical domain. |
| Outcome: | The proposed model outperforms encoders and similar sized models on the Spanish, French, and Italian benchmarks while being competitive with current state-of-the-art models in English. |
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