Diffusion-inversion probing

Approximately inverts a diffusion model's deterministic sampling process (integrating the learned velocity/score field backward from a clean sample to noise) to recover intermediate diffusion-transformer states, then fits a linear probe on those recovered states — extending linear probing to generative diffusion models whose forward pass alone doesn't expose a clean encoder representation to probe.