Inverting video diffusion transformers makes physical plausibility linearly decodable

Esmati et al. approximately invert the deterministic diffusion sampling of WAN-1.3B, CogVideoX-2B, and LTX-2B to recover intermediate states and attention maps [esmati-etal-2026-the-invisible-hand-of-physics] Physical plausibility is linearly decodable from the recovered states at ~81.27% average accuracy across IntPhys and InfLevel [esmati-etal-2026-the-invisible-hand-of-physics] This exceeds V-JEPA2 ViT-L and VideoMAE-Large baselines probed on their own forward-pass activations, so diffusion models implicitly encode physical structure recoverable only via inversion [esmati-etal-2026-the-invisible-hand-of-physics]