2 citations · 2 across the 2 of their papers we have counts for
4 papers
SocialDriveGen: Generating Diverse Traffic Scenarios with Controllable Social Interactions
Jiaguo Tian, Zhengbang Zhu, Shenyu Zhang +6
The generation of realistic and diverse traffic scenarios in simulation is essential for developing and evaluating autonomous driving systems. However, most simulation frameworks r…
DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models
Shenyu Zhang, Jiaguo Tian, Zhengbang Zhu +3
Microscopic traffic simulation has become an important tool for autonomous driving training and testing. Although recent data-driven approaches advance realistic behavior generatio…
Score-Based Diffusion Policy Compatible with Reinforcement Learning via Optimal Transport
Mingyang Sun, Pengxiang Ding, Weinan Zhang +1
Diffusion policies have shown promise in learning complex behaviors from demonstrations, particularly for tasks requiring precise control and long-term planning. However, they face…
GenSim2: Scaling Robot Data Generation with Multi-modal and Reasoning LLMs
Pu Hua, Minghuan Liu, Annabella Macaluso +4
Robotic simulation today remains challenging to scale up due to the human efforts required to create diverse simulation tasks and scenes. Simulation-trained policies also face scal…