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20212026
most citedA Survey on Multimodal Large Language Models for Autonomous Driving

27 citations · 62 across the 21 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.AI2023★ 9 cited

Personalized Autonomous Driving with Large Language Models: Field Experiments

Can Cui, Zichong Yang, Yupeng Zhou +6

Integrating large language models (LLMs) in autonomous vehicles enables conversation with AI systems to drive the vehicle. However, it also emphasizes the requirement for such syst…

cs.CL2023★ 1 cited

LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs

Yunsheng Ma, Can Cui, Xu Cao +9

Autonomous driving (AD) has made significant strides in recent years. However, existing frameworks struggle to interpret and execute spontaneous user instructions, such as "overtak…

cs.AI2023★ 27 cited

A Survey on Multimodal Large Language Models for Autonomous Driving

Can Cui, Yunsheng Ma, Xu Cao +18

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 perceive th…

cs.CV2023

MACP: Efficient Model Adaptation for Cooperative Perception

Yunsheng Ma, Juanwu Lu, Can Cui +4

Vehicle-to-vehicle (V2V) communications have greatly enhanced the perception capabilities of connected and automated vehicles (CAVs) by enabling information sharing to "see through…

cs.CV2023★ 2 cited

Radar Enlighten the Dark: Enhancing Low-Visibility Perception for Automated Vehicles with Camera-Radar Fusion

Can Cui, Yunsheng Ma, Juanwu Lu +1

Sensor fusion is a crucial augmentation technique for improving the accuracy and reliability of perception systems for automated vehicles under diverse driving conditions. However,…