WorldOracle: Benchmarking Action-Conditioned World Models against Real-World Executions

Abstract:We introduce WorldOracle, a benchmark specifically designed to evaluate action-conditioned world models (ACWMs) against paired real-world executions. Given the same initial observation and low-level action sequence, WorldOracle asks whether a predicted rollout reproduces what happens in the real world, including physical consequences and task-state transitions. We evaluate models along four complementary dimensions: physical state correctness, interaction spatial alignment, key interaction area fidelity, and multi-view action coherence. To support this evaluation, we curate real-world training and evaluation suites that cover different interaction dynamics and embodiments. The evaluation suite contains long, multi-segment episodes with both successful and failed executions, enabling evaluation across varied action outcomes and behavior distributions. Experiments on seven representative ACWMs reveal distinct model strengths and failure modes. WorldOracle provides a systematic foundation for measuring and advancing action-conditioned world modeling for manipulation. We will release the datasets, evaluation code, and leaderboard.

Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV)

arXiv:2610.18826 [cs.RO]

(or arXiv:2610.18826v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.18826 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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