DriftXpress: Faster Drifting Models via Projected RKHS Fields

ArXi:2605.12183v1 Announce Type: cross Drifting Models have emerged as a new paradigm for one-step generative modeling, achieving strong image quality without iterative inference. The premise is to replace the iterative denoising process in diffusion models with a single evaluation of a generator. However, this creates a different trade-off: drifting reduces inference cost by moving much of the computation into