really excited to finally release this one.
guidance is critical for getting flow and diffusion models to do what we want, but most methods in the literature are heuristic and work for unclear reasons. the field likes to frame it as reward-tilted sampling, yet what people run in practice is often nowhere close to that.
here we take a different angle, deriving guidance from first principles as an optimal control problem. existing methods drop out as coarse approximations, and the flow map emerges as the fundamental ingredient for effective guidance.
our approach is training-free, and reaches state-of-the-art performance across diverse benchmarks at up to 70x fewer NFEs.
amazing work by @jrrhuang, justin, kartik, and sheel.
stay tuned for more on the finetuning side!