1 citations · 1 across the 4 of their papers we have counts for
6 papers
Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving
Xin Zhou, Zongchuang Zhao, Zhibo Yang +13
We present Qwen-Drive-1.0, an initial step towards a vision-language foundation model for autonomous driving. Qwen-Drive-1.0 retains the architecture of the pretrained vision-langu…
SimWAM: A Simple World Action Model for End-to-End Autonomous Driving
Zongchuang Zhao, Xin Zhou, Tianyang Xu +6
World-Action Models (WAMs) improve end-to-end autonomous driving by transferring video dynamics priors to action prediction, but existing methods incur costly test-time future imag…
MindDrive: A Vision-Language-Action Model for Autonomous Driving via Online Reinforcement Learning
Haoyu Fu, Diankun Zhang, Zongchuang Zhao +7
Current Vision-Language-Action (VLA) paradigms in autonomous driving primarily rely on Imitation Learning (IL), which introduces inherent challenges such as distribution shift and…
NAUTILUS: A Large Multimodal Model for Underwater Scene Understanding
Wei Xu, Cheng Wang, Dingkang Liang +4
Underwater exploration offers critical insights into our planet and attracts increasing attention for its broader applications in resource exploration, national security, etc. We s…
Extending Large Vision-Language Model for Diverse Interactive Tasks in Autonomous Driving
Zongchuang Zhao, Haoyu Fu, Dingkang Liang +5
The Large Visual-Language Models (LVLMs) have significantly advanced image understanding. Their comprehension and reasoning capabilities enable promising applications in autonomous…
ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation
Haoyu Fu, Diankun Zhang, Zongchuang Zhao +7
End-to-end (E2E) autonomous driving methods still struggle to make correct decisions in interactive closed-loop evaluation due to limited causal reasoning capability. Current metho…