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SpanVLA slashes action generation latency in autonomous driving by bridging VLMs with flow-matching, while also learning from driving mistakes to boost robustness.
Autonomous driving policies that ace open-loop tests can still crash and burn in the real world, because they learn to ignore the reactive nature of closed-loop environments.
