BioMistral-NLU bridges the gap between general-purpose LLMs and specialized medical language understanding needs through targeted instruction tuning.

• Created a unified prompting format for 7 critical medical NLU tasks
• Developed a specialized instruction-tuning dataset for medical applications
• Outperforms general-purpose LLMs on medical benchmarks while maintaining broad capabilities
• Demonstrates practical zero-shot adaptability to new medical language tasks

This research matters because it enables more accurate medical text analysis without sacrificing the versatility of large language models, potentially improving clinical documentation, research analysis, and healthcare decision support.

BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuning