  How much explicit guidance is necessary for conditional diffusion? We
consider the problem of conditional sampling using an unconditional diffusion
model and limited explicit guidance (e.g., a noised classifier, or a
conditional diffusion model) that is restricted to a small number of time
steps. We explore a model predictive control (MPC)-like approach to approximate
guidance by simulating unconditional diffusion forward, and backpropagating
explicit guidance feedback. MPC-approximated guides have high cosine similarity
to real guides, even over large simulation distances. Adding MPC steps improves
generative quality when explicit guidance is limited to five time steps.
