arxiv
PublishedJune 18, 2026 at 4:00 AM
—neutral
Scaling Learning-based AEB with Massive Unlabeled Data
Publisher summary· verbatim
arXiv:2606.18864v1 Announce Type: cross Abstract: This paper studies how to scale learning-based automatic emergency braking (AEB) with massive unlabeled fleet data under production constraints. Our approach is based on meta-feedback semi-supervised learning (MF-SSL), where a teacher generates pseud
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Originally published on arxiv ↗