11 papers
Agent-driven Long-tail Simulation for Autonomous Driving
Junru Gu, Lijin Yang, Jianing Huang +3
Evaluating autonomous driving systems in closed-loop settings requires realistic and interactive simulation, yet existing simulators largely rely on log replay or rule-based agents…
BLUE: Toward Better Language Use in Efficient Vision-Language-Action Models for Autonomous Driving
George Ling, Lijin Yang, Hao Yang +1
We present BLUE, a minimal method for better language use in vision-language-action (VLA) models for autonomous driving (AD). Through extensive analysis, we reveal that language ma…
Bridging the 2D-3D Gap: A Hierarchical Semantic-Geometric Map for Vision Language Navigation
Kailing Li, Tianwen Qian, Lijin Yang +4
Vision-Language Navigation (VLN) enables embodied agents to reach target locations in unseen environments by following language instructions. Despite recent progress with vision-la…
GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation
Tianchen Deng, Xuefeng Chen, Yi Chen +8
Driving World Models (DWMs) have been developing rapidly with the advances of generative models. However, existing DWMs lack 3D scene understanding capabilities and can only genera…
Judge, Then Drive: A Critic-Centric Vision Language Action Framework for Autonomous Driving
Lijin Yang, Jianing Huang, Zhongzhan Huang +2
Recent advances in vision language action (VLA) models have shown remarkable potential for autonomous driving by directly mapping multimodal inputs to control signals. However, pre…
BridgeDrive: Diffusion Bridge Policy for Closed-Loop Trajectory Planning in Autonomous Driving
Shu Liu, Wenlin Chen, Weihao Li +7
Diffusion-based planners have shown strong potential for autonomous driving by capturing multi-modal driving behaviors. A key challenge is how to effectively guide these models for…