Ruochong Li — accepted AI-conference papers

2026

DexGraspVLA: A Vision-Language-Action Framework Towards General Dexterous Grasping

Yifan Zhong, Xuchuan Huang, Ruochong Li, Ceyao Zhang, Zhang Chen, Tianrui Guan +6

AAAI 2026technical

Dexterous grasping remains a fundamental yet challenging problem in robotics. A general-purpose robot must be capable of grasping diverse objects in arbitrary scenarios. However, existing research typically relies on restrictive assumptions, such as single-object settings or limited environments, sh

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2025

DexFlyWheel: A Scalable and Self-improving Data Generation Framework for Dexterous Manipulation

Kefei Zhu, Fengshuo Bai, YuanHao Xiang, Yishuai Cai, Xinglin Chen, Ruochong Li +5

NeurIPS 2025spotlight

Dexterous manipulation is critical for advancing robot capabilities in real-world applications, yet diverse and high-quality datasets remain scarce. Existing data collection methods either rely on human teleoperation or require significant human engineering, or generate data with limited diversity,…

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