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Achieving 93.7 on the NAVSIM v1 benchmark, CLEAR redefines the efficiency of multi-modal planning in autonomous driving without the need for complex iterative processes.
LLMs can now predict where drivers look with uncanny human-like accuracy, thanks to a new dataset and architecture that grounds attention in objects, not just scenes.
Time-to-collision metrics miss critical collision risk information, but a new 2D acceleration-based metric anticipates collisions far better.
LLMs can now handle autonomous driving tasks with greater precision and efficiency thanks to DriveCode, which replaces discrete number tokens with continuous embeddings.
