Several docking campaigns have demonstrated that virtual screening of such extensive chemical spaces can yield more diverse and potent compounds than those found in smaller in-stock libraries. However, the rapid and remarkable expansion of ultra-large virtual chemical spaces has made it impractical to enumerate and screen every compound within these spaces. Although active learning approaches can accelerate the screening process by a few orders of magnitude, the computational cost still increases linearly with library size, effectively limiting the evaluation of chemical spaces beyond billions of compounds.