Hierarchical Phase Transitions in Bayesian Flow Networks Enable Training-Free Molecular Design
Bayesian flow networks (BFNs) jointly model atomic coordinates and atom types for structure-based drug design, but their generative dynamics remain poorly understood. We show that the two channels resolve on different terms: atom types pass through a sharp commitment transition at tc1, whereas coordinate precision im...