Large language models (LLMs) have received considerable attention recently due to their
outstanding comprehension and reasoning capabilities, leading to great progress in many …

Autonomous driving has achieved significant milestones in research and development over
the last two decades. There is increasing interest in the field as the deployment of …

With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …

The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …

We study how vision-language models (VLMs) trained on web-scale data can be integrated
into end-to-end driving systems to boost generalization and enable interactivity with human …

Despite significant recent progress in the field of autonomous driving modern methods still
struggle and can incur serious accidents when encountering long-tail unforeseen events …

A primary hurdle of autonomous driving in urban environments is understanding complex
and long-tail scenarios, such as challenging road conditions and delicate human behaviors …

Human-level driving is an ultimate goal of autonomous driving. Conventional approaches
formulate autonomous driving as a perception-prediction-planning framework, yet their …

Abstract Large Vision-Language Models (LVLMs) have demonstrated remarkable
capabilities in various multimodal tasks. However their potential in the medical domain …

The applications of Vision-Language Models (VLMs) in the field of Autonomous Driving (AD)
have attracted widespread attention due to their outstanding performance and the ability to …