Researchers propose Programmable World Model for persistent world state

Proposed the Programmable World Model, which separates world-state evolution from the generation of visual observations, targeting the problem that video world models cannot maintain persistent state over long interactions. An agent translates natural-language instructions into executable programs that specify entity states and state-transition rules; a lightweight engine executes them to maintain an explicit global state that includes off-screen entities and non-visual attributes; and, with state-augmented 3D OBBs as the intermediate representation, these are deterministically compiled, together with the target camera trajectory, into pixel-aligned spatiotemporal conditioning signals for a pretrained video model. The authors claim it recorded 94% Count Accuracy and 98% State Accuracy on CombatStateBench, a benchmark they proposed, far ahead of existing interactive video world models.