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Drive. We further evaluate zero-shot transfer from real-world logs to simulation on Bench
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UNIVERSE achieves a remarkable 4.3脳 speedup in trajectory inference while maintaining planning accuracy, revolutionizing how video dynamics inform autonomous driving actions.
Ditch pixel-perfect reconstruction: LVDrive shows that learning future scene representations in a high-level latent space dramatically improves autonomous driving performance.
Autonomous driving models can now achieve remarkable zero-shot generalization by leveraging the power of large-scale video generation models to jointly predict future actions and visuals.
