WorldSimProbe is a five-suite benchmark showing that six action-conditioned world models systematically degrade in action-to-motion fidelity and interaction grounding across RoboTwin, ManiSkill, and LIBERO.
RoboTrustBench: Benchmarking the Trustworthiness of Video World Models for Robotic Manipulation
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abstract
Video world models are increasingly used in robotic manipulation, yet existing benchmarks mostly evaluate them under valid, feasible, and safe instructions. We introduce RoboTrustBench, a benchmark for evaluating the trustworthiness of video world models under four scenarios: Normal, Constraint-Sensitive, Counterfactual, and Adversarial. Built from real-world DROID episodes, RoboTrustBench contains 1,207 expert-validated instruction-image pairs and a six-dimensional evaluation protocol with 13 fine-grained criteria. Evaluating seven representative video world models with human and MLLM assessment, we find that current models often generate visually coherent videos, but struggle with constraint reasoning, counterfactual grounding, physical interaction, and unsafe-instruction suppression. These results show that visual quality and surface-level instruction following are insufficient for trustworthy robotic video world modeling.
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cs.RO 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
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WorldSimProbe: Diagnosing Simulator Faithfulness in Action-Conditioned World Models for Embodied Manipulation
WorldSimProbe is a five-suite benchmark showing that six action-conditioned world models systematically degrade in action-to-motion fidelity and interaction grounding across RoboTwin, ManiSkill, and LIBERO.