2 papers
cs.CV2026
ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving
Lin Sha, Haiyun Guo, Tao Wang +4
Vision-Language Models (VLMs) have become central to autonomous driving systems, yet their deployment is severely bottlenecked by the massive computational overhead of multi-view c…
cs.CV2025
Evaluation of Safety Cognition Capability in Vision-Language Models for Autonomous Driving
Enming Zhang, Peizhe Gong, Xingyuan Dai +3
Ensuring the safety of vision-language models (VLMs) in autonomous driving systems is of paramount importance, yet existing research has largely focused on conventional benchmarks…