Ruoxuan Yang — accepted AI-conference papers

2024

Driving Style Alignment for LLM-powered Driver Agent

Ruoxuan Yang, Xinyue Zhang, Anais Fernandez-Laaksonen, Xin Ding, Jiangtao Gong

IROS 2024poster

Recently, LLM-powered driver agents have demonstrated considerable potential in the field of autonomous driving, showcasing human-like reasoning and decision-making abilities. However, current research on aligning driver agent behaviors with human driving styles remains limited, partly due to the sc…

Cited by 12 Source ↗Scholar ↗

2024

SurrealDriver: Designing LLM-powered Generative Driver Agent Framework based on Human Drivers’ Driving-thinking Data

Ye Jin, Ruoxuan Yang, Zhijie Yi, Xiaoxi Shen, Huiling Peng, Xiaoan Liu +6

IROS 2024poster

Leveraging advanced reasoning capabilities and extensive world knowledge of large language models (LLMs) to construct generative agents for solving complex real-world problems is a major trend. However, LLMs inherently lack embodiment as humans, resulting in suboptimal performance in many embodied d…

Cited by 9 Source ↗code ↗Scholar ↗