World Model Evaluation

World Model Evaluation studies whether a model captures how an environment changes, especially when an agent acts or observations are missing. Approaches include open-loop prediction metrics, action-conditioned rollouts, closed-loop policy tests, physics-grounded diagnostics, and human or vision-language model judging. Benchmarks span robotic manipulation such as LIBERO and RoboTwin, driving such as NuPlan, and interactive GUI, web, and game environments. A central challenge is that visual realism and one-step accuracy often fail to predict physical consistency, long-term reliability, or planning success, so evaluation remains fragmented across tasks and horizons.