MNIST-PRO transforms classic MNIST digit recognition into a sequential, glimpse-based search task under partial observability, evaluating how multimodal models construct and maintain perceptual state across four memory representations during active sensing. The benchmark reveals large performance gaps under partial observability, identifying three failure modes: difficulty integrating fragmented visual evidence, premature exploration termination, and failure to revise incorrect initial beliefs.
