dailyai.report

Categorical Flow Maps (CFMs) enable discrete data generation through a continuous flow matching process between Gaussian and one-hot distributions. Apple researchers demonstrate that this approach allows for accelerated sampling and tilting. This offers a viable alternative to autoregressive language modeling. Practitioners can now generate discrete sequences with significantly faster inference speeds.