TOAD applies test-time Cross-Entropy Method optimization to refine trajectories using the planner's scorer as a reward function, improving end-to-end autonomous driving performance without retraining.
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
CLEAR achieves state-of-the-art PDMS of 93.7 on NAVSIM v1 by combining single-step VAE latent drift with Qwen 3.5-guided adaptive scheduling and trajectory scoring for end-to-end driving.
citing papers explorer
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Test-Time Trajectory Optimization for Autonomous Driving
TOAD applies test-time Cross-Entropy Method optimization to refine trajectories using the planner's scorer as a reward function, improving end-to-end autonomous driving performance without retraining.
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CLEAR: Cognition and Latent Evaluation for Adaptive Routing in End-to-End Autonomous Driving
CLEAR achieves state-of-the-art PDMS of 93.7 on NAVSIM v1 by combining single-step VAE latent drift with Qwen 3.5-guided adaptive scheduling and trajectory scoring for end-to-end driving.