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The paper proposes BiRG-LoRA, a rank-gated LoRA method for medical question answering that uses clinically structured priors to select sparse rank subsets, achieving 69.31% macro-average accuracy across four benchmarks while using fewer parameters than mixture-of-experts approaches.