arXiv Artificial Intelligence

Towards Reliable Vision-Language Models for Autonomous Driving

1 hour ago 02.10.2026 07:00 👁 1 views
Towards Reliable Vision-Language Models for Autonomous Driving

Quick summary

arXiv:2610.01531v1 Announce Type: new Abstract: Vision-Language models (VLMs) are increasingly being explored in autonomous driving for tasks such as scene understanding, driving reasoning, decision-making, and end-to-end driving. As their role becomes more prominent, ensuring their robustness and reliability is increasingly important. In real-world conditions, visual inputs may be degraded by sensor imperfections and environmental conditions, potentially affecting both model predictions and their associated confidence. Such degradation is especially concerning in autonomous driving, where saf

Key takeaways

  • arXiv:2610.01531v1 Announce Type: new Abstract: Vision-Language models (VLMs) are increasingly being explored in autonomous driving for tasks such as scene understanding, driving reasoning, decision-making, and end-to-end driving.
  • As their role becomes more prominent, ensuring their robustness and reliability is increasingly important.
  • In real-world conditions, visual inputs may be degraded by sensor imperfections and environmental conditions, potentially affecting both model predictions and their associated confidence.

Why it matters

“Towards Reliable Vision-Language Models for Autonomous Driving” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗