Apple Publishes NeurIPS Paper on Fast Image Generation That Keeps Exact Likelihood Math
Apple researchers, with collaborators from the University of Pennsylvania and UIUC, introduced a new generative modeling technique called Normalizing Trajectory Models (NTM) in a paper accepted at NeurIPS. Unlike typical diffusion models that rely on many small Gaussian denoising steps, NTM treats each step as a flexible, invertible transformation that preserves exact probability calculations — something most fast few-step generation methods give up when they rely on distillation or adversarial training. According to the paper, NTM can match or beat strong text-to-image baselines using only four sampling steps.