1 citations · 1 across the 7 of their papers we have counts for
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Explicit Geometric Chain-of-Thought for Vision-Language-Action in Autonomous Driving
Xingtai Gui, Yucheng Zhou, Dongqian Guo +3
Vision-language-action~(VLA) models have emerged as a promising paradigm for autonomous driving. However, existing VLA models still suffer from a fundamental mismatch: driving acti…
ChainFlow-VLA: Causal Flow Planning with Vision-Language Models
Xiyang Wang, Xinlin Wang, Tingguang Zhou +7
Current end-to-end autonomous driving systems are fundamentally limited by a mismatch between temporal causal reasoning and global trajectory consistency. Autoregressive (AR) model…
Bridging Scene Generation and Planning: Driving with World Model via Unifying Vision and Motion Representation
Xingtai Gui, Meijie Zhang, Tianyi Yan +5
End-to-end autonomous driving aims to generate safe and plausible planning policies from raw sensor input. Driving world models have shown great potential in learning rich represen…
From Human Intention to Action Prediction: Intention-Driven End-to-End Autonomous Driving
Huan Zheng, Yucheng Zhou, Tianyi Yan +9
While end-to-end autonomous driving has achieved remarkable progress in geometric control, current systems remain constrained by a command-following paradigm that relies on simple…