WorldRoamBench: An Open-World Benchmark for Long-Horizon Stability of Interactive World Models

The benchmark comprises 1000+ test cases across Nature, Urban, and Indoor scenes in first/third-person views with WASD 10-60 s continuous interaction. It comes from a paper posted to arXiv on 21 September 2026. Despite rapid progress in interactive world models (IWMs), short-horizon performance does not establish sustained action following, visual stability, physical plausibility, or memory. We introduce WorldRoamBench, an open-world benchmark for long-horizon stability across four dimensions, each with innovations: (i) Action: per-frame action metric bypassing cross-model semantic scale disparity and exposing failures hidden by trajectory; (ii) Vision: sliding-window drift metric capturing non-monotonic mid-sequence collapse missed by start-vs-end comparisons; (iii) Physics: evaluation of physical plausibility across mechanics, optics, and 3D consistency, gated by camera-motion and subject-tracking checks; (iv) Memory: a trajectory-aware protocol reducing confounding from action-following errors, evaluating scene memory via transition-localized 3D point-cloud reconstruction and subject memory via tracking-plus-VLM reasoning. Evaluating 10+ open/closed-source models reveals none reliably satisfies all dimensions; even the best achieves only moderate scores. Advances on WorldRoamBench are steps toward IWMs that are stable, physically grounded, memory-faithful, and deployable in real-world applications.

Why it counts

The benchmark comprises 1000+ test cases across Nature, Urban, and Indoor scenes in first/third-person views with WASD 10-60 s continuous interaction.

Sources

Primary source: primary source

What is not known

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