CURE-MED-14B: Multilingual Medical Reasoning LLM
CURE-MED-14B is a 14 billion parameter large language model developed by Aikyam Lab and collaborators, specifically designed for multilingual medical reasoning. Built upon the Qwen/Qwen2.5-14B-Instruct model, it addresses the complexities of medical queries across diverse languages.
Key Capabilities & Features
- Multilingual Medical Reasoning: Specialized for open-ended medical questions in 13 languages, including Amharic, Yoruba, and Swahili.
- Curriculum-Informed Reinforcement Learning: Employs a unique approach integrating code-switching-aware supervised fine-tuning (SFT) and Group Relative Policy Optimization (GRPO) to improve logical correctness and language stability.
- Enhanced Performance: Designed to overcome challenges in multilingual medical reasoning, particularly in underrepresented languages.
- Robust Training & Evaluation: Trained and evaluated using CUREMED-BENCH, a high-quality multilingual benchmark with verifiable answers.
Good For
- Healthcare Applications: Ideal for medical reasoning tasks requiring high accuracy and language stability.
- Multilingual Support: Suitable for use cases needing to process medical information across a wide range of languages, including those with limited existing LLM support.
- Research & Development: Provides a strong foundation for further research into multilingual medical AI and reinforcement learning techniques.