Suppose that we exactly know the constraint-satisfying set X * D . Depending on the constraints, it may be highly likely that sampling k compounds uniformly at random from X * D results in far fewer than k distinct compound clusters, e.g., when using Butina clustering with ECFP4 similarity. This can happen when the library includes clusters that contain a very large number of analogues that are constraint-satisfying. For the policy, this can manifest in probability density being more heavily concentrated in regions where many latent codes map to compounds that earn a large (expected) reward, such that sampling i.i.d. from the policy induces compound sets that are surprisingly lacking in diversity, even if the policy has correctly identified other relevant modes.