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A metric interaction framework that models object-level and scene-level interactions in physical Cartesian space at a shared metric scale and improves diverse VLA and WAM baselines with a small number of additional parameters and training steps is introduced.
Robots can now learn to manipulate dynamic environments effectively from just one static demonstration, drastically improving performance and efficiency.