collaborators

8 papers

cs.CV2026

Xiaomi OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation

Jinghui Lu, Jiayi Guan, Zhijian Huang +47

Chain-of-Thought (CoT) reasoning has become a powerful driver of trajectory prediction in VLA-based autonomous driving, yet its autoregressive nature imposes a latency cost that is…

cs.CV2026

PhysInOne: Visual Physics Learning and Reasoning in One Suite

Siyuan Zhou, Hejun Wang, Hu Cheng +36

We present PhysInOne, a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike existing datasets limited to mere…

cs.CV2026

UniDriveVLA: Unifying Understanding, Perception, and Action Planning for Autonomous Driving

Yongkang Li, Lijun Zhou, Sixu Yan +11

Vision-Language-Action (VLA) models have recently emerged in autonomous driving, with the promise of leveraging rich world knowledge to improve the cognitive capabilities of drivin…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…