Author

Duan-Feng Chu

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Review Oct 2026

LIBERO-Pro2.0: A Benchmark for Evaluating the Robustness of Embodied Foundation Models

LIBERO has emerged as a widely adopted benchmark for evaluating robotic manipulation policies. However, strong performance on LIBERO does not necessarily indicate robust embodied capabilities, as models may exploit benchmark-specific regularities rather than generalize to diverse operating conditions. In this work, we...

Xue-Yang Zhou, Yang-Ming Xu, Qian-Jiang Li et al. · 0 citations

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

S-squared-VLA: Decoupling Semantic and Spatial Streams in Vision-Language-Action Models for Autonomous Driving

The S-squared-VLA is proposed, which explicitly decouples the semantic and spatial streams in Vision-Language-Action models, and significantly outperforms baselines, achieving the highest No Collision rate among all evaluated methods.

Jianguo Yu, Rukang Wang, Duan-Feng Chu et al. · arXiv.org · 0 citations