Risk-Calibrated Proposal Transport for Finite-Particle Diffusion Steering
Inference-time steering combines pretrained diffusion experts or rewards without retraining by changing the dynamics that transport noise to data. Feynman-Kac correction compensates for proposal mismatch through importance-weighted sequential Monte Carlo (SMC), whose finite-particle behavior depends on the proposal. Va...
Ziseok Lee, JaeHyeong Kim, Seungwon Kim et al.
· 0 citations