dailyai.report

Apple researchers developed a method to scale Categorical Flow Maps for discrete data generation. This approach replaces autoregressive language modeling with continuous flow matching between Gaussian and one-hot distributions. It enables faster sampling and tilting capabilities. Practitioners can now generate discrete text sequences with the efficiency typically reserved for continuous image or audio models.