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RoboWorM: A Benchmark for Evaluating Motion Realism and Acceleration Effects in Embodied Video World Models

The authors propose RoboWorM, a deployment-aware benchmark for robotic manipulation video world models that examines structural and spatiotemporal fidelity using hardware priors such as robot kinematic trees and fixed camera configurations. The benchmark collects 1,605 episodes across single-arm, bimanual, and humanoid morphologies, covering Markovian and long-horizon non-Markovian tasks under single-view and multi-view setups, and proposes two deterministic metrics that do not rely on vision-language models: KIVA and RIGIS.

Part of the event: RoboWorM: An Embodied Video World Model Evaluation Benchmark Released

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