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  # Med-PRM-Reward (Version 1.0)
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- 🚀 Med-PRM-Reward is among the first Process Reward Models (PRMs) specifically designed for the medical domain. Unlike conventional PRMs, it enhances its verification capabilities by integrating clinical knowledge through retrieval-augmented generation (RAG). Med-PRM-Reward demonstrates exceptional performance in scaling-test-time computation, particularly outperforming majority‐voting ensembles on complex medical reasoning tasks. Moreover, its scalability is not limited to Llama-3.1-8B-Instruct: it delivers similarly outstanding results in scaling-test-time computation across multiple other medical‐specialized models. Notably, when combined with llama-3-meerkat-8b-v1.0, it became the first sub-10B small language model to surpass a score of 80 on the MedQA (4-option) benchmark.
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  📄 Paper: [Med-PRM-Reward: Medical Reasoning Models with Stepwise, Guideline‑verified Process Rewards](https://arxiv.org/abs/2506.11474)
 
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  # Med-PRM-Reward (Version 1.0)
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+ 🚀 Med-PRM-Reward is among the first Process Reward Models (PRMs) specifically designed for the medical domain. Unlike conventional PRMs, it enhances its verification capabilities by integrating clinical knowledge through retrieval-augmented generation (RAG). Med-PRM-Reward demonstrates exceptional performance in scaling-test-time computation, particularly outperforming majority‐voting ensembles on complex medical reasoning tasks. Moreover, its scalability is not limited to Llama-3.1-8B-Instruct: it delivers similarly outstanding results in scaling-test-time computation across multiple other medical‐specialized models. Notably, when combined with llama-3-meerkat-8b-v1.0, it became the first 8B model framework to surpass a score of 80 on the MedQA (4-option) benchmark.
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  📄 Paper: [Med-PRM-Reward: Medical Reasoning Models with Stepwise, Guideline‑verified Process Rewards](https://arxiv.org/abs/2506.11474)