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cs.RO2026
Less Language, More Latents: Annotation-Efficient VLAs for Driving
Alexey Zakharov, Kemal Oksuz, Puneet K. Dokania
Vision-language-action models (VLA) promise human-steerable autonomous driving, but their training is bottlenecked by the scarcity of frames paired with natural-language instructio…
cs.LG2026
Conformalized Large Language Models under Configuration Shift
Yuqicheng Zhu, Jialin Yu, Lin Li +7
Conformal prediction (CP) is a distribution-free framework for uncertainty quantification that has recently been adapted to large language models (LLMs), providing prediction sets…