World models trained on expert trajectories struggle to generalize to new combinations of familiar states and actions—a critical limitation for real-world planning that requires handling novel situations built from known components.
This paper introduces AnyGoal, a benchmark for testing whether world models can generalize beyond their training data by recombining familiar state and action factors in new ways.