86 citations · 250 across the 17 of their papers we have counts for
5 papers · 1 filter
DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving
Yingyan Li, Shuyao Shang, Weisong Liu +10
Scaling Vision-Language-Action (VLA) models on large-scale data offers a promising path to achieving a more generalized driving intelligence. However, VLA models are limited by a `…
DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Driving
Shuyao Shang, Yuntao Chen, Yuqi Wang +2
End-to-end autonomous driving has substantially progressed by directly predicting future trajectories from raw perception inputs, which bypasses traditional modular pipelines. Howe…
UIPro: Unleashing Superior Interaction Capability For GUI Agents
Hongxin Li, Jingran Su, Jingfan Chen +4
Building autonomous agents that perceive and operate graphical user interfaces (GUIs) like humans has long been a vision in the field of artificial intelligence. Central to these a…
Unified Vision-Language-Action Model
Yuqi Wang, Xinghang Li, Wenxuan Wang +5
Vision-language-action models (VLAs) have garnered significant attention for their potential in advancing robotic manipulation. However, previous approaches predominantly rely on t…
AutoGUI: Scaling GUI Grounding with Automatic Functionality Annotations from LLMs
Hongxin Li, Jingfan Chen, Jingran Su +3
User interface understanding with vision-language models (VLMs) has received much attention due to its potential for enhancing software automation. However, existing datasets used…