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Interaction response can be harnessed to accurately calibrate material properties of 3D Gaussian representations, outperforming traditional methods by a substantial margin.
Policies may succeed in tasks but still violate deformation tolerances, revealing a critical gap in current evaluation methods for deformable-object manipulation.
Training-Distribution Hallucination is a critical challenge in robot manipulation, but ST-WAM's innovative use of DINOv3 features dramatically boosts performance under visual shifts.
