We propose a scalable and sample-efficient framework for training diffusion samplers by integrating classical sampling methods, suitable for practical applications like molecular conformer generation.

We introduce the Non-equilibrium Annealed Adjoint Sampler (NAAS), a novel SOC-based diffusion sampler that leverages annealed reference dynamics