# Kinematic Causal Attribution

Before deployment, a 4D point-cloud action model cannot say whether it relies on how a body part moves or on what shape it has. Kinematic Causal Attribution queries only model outputs and splits each spacetime region's importance into a motion term and a geometry term using two interventions: freezing motion and removing shape. On three official backbones trained on MSR-Action3D, the same arm's motion share is 0.83 versus 0.60, 0.86 versus 0.30 and 0.92 versus 0.61 across motion and shape tasks, while a model-blind motion prior marks the arm identically in both.

Before deployment, a 4D point-cloud action model cannot say whether it relies on how a body part moves or on what shape it has. Kinematic Causal Attribution queries only model outputs and splits each spacetime region's importance into a motion term and a geometry term using two interventions: freezing motion and removing shape. On three official backbones trained on MSR-Action3D, the same arm's motion share is 0.83 versus 0.60, 0.86 versus 0.30 and 0.92 versus 0.61 across motion and shape tasks, while a model-blind motion prior marks the arm identically in both.