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The paper introduces Physics-Unrolled Hybrid Neural Operator (PU-HNO), a model that predicts high-fidelity indoor radio maps from low-fidelity ray-tracing outputs by capturing propagation effects like reflection, diffraction, and scattering, outperforming existing baselines.