AI RESEARCH
DriveMA: Driving Vision-Language-Action Models with verifiable Meta-Actions
arXiv CS.CV
•
ArXi:2605.31271v1 Announce Type: new Driving Vision-Language-Action Models (Driving VLAs) aim to use language to improve end-to-end planning, but the language-action gap limits this promise. We propose DriveMA, a Driving VLA framework built on verifiable meta-actions, which summarize future ego motion into compact language-domain intentions and can be constructed from expert trajectories with a trajectory-grounded annotation pipeline and can be verified against generated trajectories through rule-based projection. DriveMA exploits this verifiability with action-centric supervised.