Asymptotically Exact Negative Guidance of Diffusion Models via Positive-Unlabeled Learning

Negative guidance of diffusion models generates samples that avoid an undesired condition, specified either by reference samples or by a conditional score alongside an unconditional model. Existing methods inject repulsive terms derived from local information at each sample, so the resulting sampler