S^2: Sensorimotor Alignment as an Offline Proxy for Embodied Policy Success

The study proposes a training-free offline metric, Sensorimotor Alignment (S^2), that measures how well a model's sensory representations align with the geometry of physical motion. The authors report that S^2 correlates positively with downstream robot task success across model families, and that it can be used to screen models before closed-loop evaluation and to identify promising VLM backbones before costly VLA fine-tuning.