Jia Hu

Criticality-Aware Gen-AI Inference via Dynamic Step Control in Resource-Efficient Vehicular Computing

Jinmei Shu, Jia Hu, Geyong Min, Zhu Xiao, Hongbo Jiang

TL;DR: A Criticality-aware Resource-efficient Inference (CARIN) framework, where inference steps are dynamically adjusted to balance delay and quality for multi-criticality tasks, is developed.

Integrating Generative AI (Gen-AI) into vehicular computing can significantly enhance road safety and driving experience. The performance of Gen-AI inference in vehicular computing is highly sensitive to the number of inference steps, where even minor adjustments can disrupt the…Read more

WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving

Xuerun Yan, Zhexi Lian, Nuoheng Zhang, Shiyu Fang, Haoran Wang, Chen Lv, et al.

Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving. However, existing methods either lack comprehensive world cognition or suffer from fragmented world foresight, inherently confining these models to reactive driving. To address this limitation, we pr…Read more