Author

Jaeha Song

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#artificial intelligence Preprint Sep 2026

Planning-Aligned Pretraining of BEV Representations with Sparse Action-Conditioned Targets for End-to-End Autonomous Driving

PAVER, Planning-Aligned BEV Encoder Pretraining is introduced, where from a single LiDAR sweep, PAVER constructs sparse risk and unknown targets describing occupied and unobserved evidence along rule-based ego motions, preserving the downstream architecture and camera-only inference.

Jaeha Song, Soonmin Hwang · 0 citations