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Command-inconsistent memory can lead to a 15.6% increase in collision rates during autonomous driving, but MomADv2 effectively filters this noise for safer long-horizon planning.
StableDrive slashes collision rates by over 23% while redefining how historical context is leveraged in autonomous driving.
Supervising latent representations at the reasoning-process level leads to a breakthrough in multimodal reasoning, outperforming traditional methods by a significant margin.
By fusing a world model with a vision-language model, MindDrive achieves state-of-the-art autonomous driving performance, suggesting a promising path toward interpretable and cognitively guided systems.
