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Preprint Sep 2026

R2S-Eval: Robot Evaluation with Real-to-Sim Calibration via Vision-Language Models

Evaluating robot manipulation policies is becoming increasingly important as generalist models, particularly vision-language-action (VLA) models, are deployed on physical robots. However, conventional real-world evaluation remains labor-intensive, unstable, and insufficiently informative. It requires repeated hardware...

Yi-Di Wang, Fei-Xiang Ruan, Ruo-Qu Chen et al. · 1 citation
#reinforcement learning Review Open access Sep 2026

Recent Advances of Reinforcement Learning Algorithms for Autonomous Driving System

This survey examines RL-based AD in modular and end-to-end pipelines and relates reported methods to task formulation and deployment evidence and examines deployment barriers, including safety, Sim2Real generalization, data efficiency, computation, embodied alignment, and evaluation readiness.

B. Shuai, Min Hua, Le-Tian Tao et al. · 0 citations

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