Qing Li

A model-free Bayesian clustering framework generates a martingale posterior over clusterings without explicit likelihoods or MCMC, effectively handling irregular shapes and noise.

Treating pretrained vision embeddings as temporary scaffolding to inject and internalize—rather than passive alignment targets—slashes diffusion transformer training budgets by over 43×.