12 citations · 30 across the 8 of their papers we have counts for
8 papers
KoMA: Knowledge-driven Multi-agent Framework for Autonomous Driving with Large Language Models
Kemou Jiang, Xuan Cai, Zhiyong Cui +7
Large language models (LLMs) as autonomous agents offer a novel avenue for tackling real-world challenges through a knowledge-driven manner. These LLM-enhanced methodologies excel…
OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text
Qingyun Li, Zhe Chen, Weiyun Wang +37
Image-text interleaved data, consisting of multiple images and texts arranged in a natural document format, aligns with the presentation paradigm of internet data and closely resem…
OASim: an Open and Adaptive Simulator based on Neural Rendering for Autonomous Driving
Guohang Yan, Jiahao Pi, Jianfei Guo +14
With deep learning and computer vision technology development, autonomous driving provides new solutions to improve traffic safety and efficiency. The importance of building high-q…
LimSim++: A Closed-Loop Platform for Deploying Multimodal LLMs in Autonomous Driving
Daocheng Fu, Wenjie Lei, Licheng Wen +5
The emergence of Multimodal Large Language Models ((M)LLMs) has ushered in new avenues in artificial intelligence, particularly for autonomous driving by offering enhanced understa…
Towards Knowledge-driven Autonomous Driving
Xin Li, Yeqi Bai, Pinlong Cai +14
This paper explores the emerging knowledge-driven autonomous driving technologies. Our investigation highlights the limitations of current autonomous driving systems, in particular…
LimSim: A Long-term Interactive Multi-scenario Traffic Simulator
Licheng Wen, Daocheng Fu, Song Mao +4
With the growing popularity of digital twin and autonomous driving in transportation, the demand for simulation systems capable of generating high-fidelity and reliable scenarios i…