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Geometry-Aware Diffusion Guidance via Curvature-Adaptive Tubular Correction
Gradient-guided diffusion samplers provide flexible priors for inverse problems and conditional generation, but strong guidance can move the sampling trajectory into regions where the learned score is poorly supported. Existing tangent-projection strategies limit first-order departure from an iso-de
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