Author

Xiang Bai

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Preprint Aug 2026

Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving

Experiments demonstrate strong 3D perception and driving scene understanding while largely preserving general vision-language capability and comprehensive evaluations across open-loop, pseudo-closed-loop, and closed-loop settings further show highly competitive motion-planning performance.

Xin Zhou, Zongchuang Zhao, Zhibo Yang et al. · 9 citations · ⚡2

Jul 2026

TurboVLA: Real-Time Vision-Language-Action Model at 32 Hz on an RTX 4090 with <1 GB VRAM

TurboVLA is introduced, a new VLA paradigm that reformulates the conventional LLM-centric pathway as a direct VLA mapping, and constructs task-conditioned representations directly from visual and linguistic features, significantly reducing the computational and memory costs of VLA inference.

Heng-Yi Xie, Chen-Fei Yao, Xian Wu et al. · arXiv.org · 6 citations · ⚡2

Preprint Aug 2026

SimWAM: A Simple World Action Model for End-to-End Autonomous Driving

SimWAM, a simple yet effective WAM that leverages future-video prediction as a training-time supervision signal, co-trains a pretrained video expert and a lightweight action expert with joint flow matching and applies reinforcement learning to optimize a compositional driving reward beyond trajectory imitation.

Zongchuang Zhao, Xin Zhou, Tianyang Xu et al. · 4 citations