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RankE introduces an end-to-end post-training framework for discrete text-to-image generation that jointly optimizes both the generator and decoder to address the latent covariate shift problem, improving alignment and fidelity simultaneously.
Introduces Discrete MeanFlow, a method for one-step generation in discrete state spaces by learning conditional transition kernels of continuous-time Markov chains, avoiding iterative denoising.