AdaVoMP predicts accurate spatially-varying Young's modulus, Poisson's ratio, and density for 3D objects across resolutions. It uses a sparse, adaptive voxel structure and a sparse transformer encoder-decoder to achieve 16^3 times higher resolution than prior methods, with improved accuracy and lower test-time compute.