Abstract Multimodal Large Language Models (MLLMs) have recently demonstrated
impressive capabilities in multimodal understanding reasoning and interaction. However …

The fusion of human-centric design and artificial intelligence capabilities has opened up
new possibilities for next-generation autonomous vehicles that go beyond traditional …

Multimodal large language models (MLLMs) are designed to process and integrate
information from multiple sources such as text speech images and videos. Despite its …

This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …

In the vast and dynamic landscape of urban settings Traffic Safety Description and Analysis
plays a pivotal role in applications ranging from insurance inspection to accident prevention …

Vision-language generative AI has demonstrated remarkable promise for empowering cross-
modal scene understanding of autonomous driving and high-definition (HD) map systems …

Large Vision-Language Models (LVLMs), due to the remarkable visual reasoning ability to
understand images and videos, have received widespread attention in the autonomous …

Diffusion models excel at modeling complex and multimodal trajectory distributions for
decision-making and control. Reward-gradient guided denoising has been recently …

Vision language models (VLMs) have shown impressive capabilities across a variety of
tasks, from logical reasoning to visual understanding. This opens the door to richer …

Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of
intelligent modules in the Internet of Vehicles (IoV) by synthesizing augmented datasets …