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Expand-and-Prune: Test-Time Candidate-Space Adaptation for End-to-End Autonomous Driving
Candidate-based end-to-end driving planners reason over a finite set of trajectory hypotheses. However, for sparse planners, a limited candidate set may provide insufficient support for scene-relevant maneuvers, while fixed downstream candidate budgets do not account for prediction uncertainty. To a
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