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Less Language, More Latents: Annotation-Efficient VLAs for Driving

Zakharov, Alexey et al.
arXiv (All) · Papers
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robotics
Vision-language-action models (VLA) promise human-steerable autonomous driving, but their training is bottlenecked by the scarcity of frames paired with natural-language instructions: while camera streams and expert trajectories are logged at scale, language annotations (e.g., turn left at the inter
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