Bidirectional diffusion models predict rollout errors via round-trip consistency

A new training method for latent diffusion models uses bidirectional consistency to estimate cumulative errors in long-sequence generation. The approach allows models to self-evaluate rollout accuracy in deployment scenarios where ground truth data is unavailable.