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From Likelihood to Utility: Quality-Axis Diffusion for End-to-End Autonomous Driving
Diffusion models have become a dominant paradigm for end-to-end autonomous driving, yet existing planners organize trajectory generation along the Gaussian-noise axis, treating driving utility only as an auxiliary guidance or selection signal. We instead formulate diffusion along a driving-quality a
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