SpanVLA: Learning from Negative-Recovery Samples with Fast Action Bridging for Vision-Language-Action Model
SpanVLA is an autonomous driving framework that uses a Vision-Language Model to plan actions. It introduces an efficient action bridge using flow matching to speed up trajectory generation, significantly reducing latency. Furthermore, it improves safety by training on real-world negative and recovery driving samples, teaching the model how to avoid mistakes and recover from them.