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Visual fidelity in World Models can be misleading; a model that looks better may perform worse in action robustness, challenging existing evaluation paradigms.
World models may be fundamentally misinterpreting future states, imagining them kinematically rather than dynamically, leading to significant long-horizon failures.
A 4B-parameter model outperforms Gemini-3-Pro in autonomous driving by incorporating physics-informed constraints and style-aware training, suggesting specialized models can surpass larger, general-purpose models in domain-specific tasks.
