m1 is a novel approach that leverages test-time scaling techniques to significantly improve large language models' medical reasoning capabilities without requiring model retraining.

• Demonstrates that test-time scaling can be effectively adapted from mathematical reasoning to medical domains
• Introduces a simple yet effective methodology that boosts medical question-answering performance
• Provides the first comprehensive investigation of scaling techniques specifically optimized for medical knowledge representation
• Achieves substantial performance gains across multiple medical reasoning benchmarks

This research enables healthcare organizations to extract more accurate medical insights from existing LLMs, potentially improving clinical decision support and medical education tools while reducing implementation costs.

m1: Unleash the Potential of Test-Time Scaling for Medical Reasoning with Large Language Models