Robot foundation models are typically evaluated through costly closed-loop rollouts, motivating low-cost offline proxies for model capability. The Platonic Representation Hypothesis (PRH) suggests tha
Sensorimotor alignment measures how sensory representations match physical motion geometry, serving as a low-cost offline predictor of robot model performance.
Robot foundation models are typically evaluated through costly closed-loop rollouts, motivating low-cost offline proxies for model capability. The Platonic Representation Hypothesis (PRH) suggests that as representations improve, modalities such as vision and language converge toward a shared statistical model of reality. We ask whether motion trajectories form another such modality: as embodied models become more capable, should their sensory representations converge toward the structure of physical motion? To test this, we propose Sensorimotor Alignment (S^2), a training-free offline metric that measures how well a model's sensory representation aligns with the geometry of physical…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
Sensorimotor Alignment: A Platonic Proxy for Embodied Policy Success was first seen on Hugging Face · Daily papers on Oct 29, 2026. Since then it has appeared in 16 checks on 2 different days. Its best position was #8 of 30, reached on Oct 30, 05:28 UTC. It dropped off the list after Oct 30, 15:28 UTC.
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Not at the moment. It was last on the list on Oct 30, 15:28 UTC, after 2 days of trending.
#8 on Hugging Face · Daily papers, on Oct 30, 05:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 29, 2026 and has been on the list on 2 days (16 checks) since.