dailyai.report

Apple researchers developed Categorical Flow Maps to generate discrete data using continuous flow matching. This method enables accelerated sampling and tilting, offering a viable alternative to autoregressive language modeling. The approach bridges the gap between continuous modalities and discrete text. Practitioners can now achieve faster inference without sacrificing sample quality.