2026
Flow Expansion via Verifier-Constrained Noised State Space Exploration
ICLR 2026poster
Flow and diffusion models are typically pre-trained on limited available data (e.g., molecular samples), covering only a fraction of the valid design space (e.g., the full molecular space). As a consequence, they tend to generate samples from only a narrow portion of the feasible domain. This is a f…