UnpredictaBench Tests LLM Calibration to Target Distributions, Not Just Diversity

UnpredictaBench evaluates whether LLMs can sample from specified target distributions — canonical statistical distributions, stochastic programs, and natural distributions — distinguishing calibrated randomness from mere output diversity. Targets the use case of LLMs as simulation agents where distribution collapse causes systematic bias.