Author

Zhenxuan Fan

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Preprint Sep 2026

IronMind: Scaling Humanoid Dexterous Manipulation via Camera-Space Ego-Centric Pretraining

Egocentric human video offers a scalable data source for dexterous manipulation, yet using it to train humanoid robots presents two challenges: (1) an embodiment gap, as human hands differ structurally from robot end-effectors and low-cost egocentric recordings lack the torso kinematics required by conventional retarge...

Hui-Min Pan, Y. Ren, Kun-Peng Song et al. · 0 citations

#artificial intelligence Preprint Sep 2026

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchmarks mainly evaluate task completion under predefined settings, offering limited insight into model reasoning under increasing spatial and procedural complexity. We introd...

Zhen-Xuan Fan, Bo Zhang, Yu-Tong Lin et al. · 0 citations

#artificial intelligence Preprint Sep 2026

EmbodiedSkills: A Unified Framework for Orchestrating, Training, and Deploying VLA Agents

EmbodiedSkills is a unified framework that treats each skill decision as an execution proposal: the runtime checks its prerequisites before execution and verifies the outcome afterward and provides a trainable and inspectable agent layer for turning low-level VLA policies into closed-loop embodied systems.

Wei Wang, Wen-Qiao Zhang, Yu-Tong Lin et al. · 2 citations