policy
Awesome-XPU-Autonomous-Driving
Kunlunxin-AD · PyTorch
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Overview
Name
Awesome-XPU-Autonomous-Driving
Author
Kunlunxin-AD
Framework
PyTorch
License
Apache-2.0
Skill type
other
Evidence level
untested
Task description
A comprehensive list of state-of-the-art papers in autonomous driving and robotics, covering end-to-end (e2e) learning, vision-language models (VLM), vision-language-action models (VLA), world models, and reinforcement learning (RL), with links to papers, code repositories, and relevant websites.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
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Compatible environments
0No environments list Awesome-XPU-Autonomous-Driving yet.
Datasets that reference this policy
0No datasets reference Awesome-XPU-Autonomous-Driving yet.