September 25, 2025Open Access

MedGR²: Breaking the Data Barrier for Medical Reasoning via Generative Reward Learning

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MedGR$^2$ improves data generation for medical reasoning, enhancing model performance and generalization.
Experiments show supervised fine-tuning with MedGR$^2$ data surpasses traditional human-curated datasets.
The framework utilizes generative reward learning to create a data generator and reward model, enabling efficient learning.
MedGR$^2$ demonstrates state-of-the-art performance in cross-modality tasks with fewer resources compared to larger models.

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Generative reward learning enhances medical data generation and reinforcement learning, indicating potential for better AI.

Zhi et al. (2025) studied this question.

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