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Explicitly modeling depth in world-action models significantly boosts planning robustness and future prediction quality for autonomous driving.
DrivingGen reveals that current generative driving world models either look good but break physics, or capture motion realistically but lack visual fidelity, exposing a critical trade-off for autonomous driving applications.
