Why did previous continuous diffusion struggle?
Standard trajectories waste over 90% of the optimization budget. Tokens retain their original identity for most of the noising trajectory, then collapse abruptly in a tiny window near the end!
Previous schedules allocated training steps uniformly, training the model where token identity didn't even change.