likelihood-training

This paper introduces Normalizing Trajectory Models (NTM), a novel approach to diffusion-based generation that models reverse steps as conditional normalizing flows with exact likelihood training. NTM enables high-quality text-to-image generation in just four steps while retaining the likelihood framework, outperforming baselines on standard benchmarks.