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Shunlin Lu

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#artificial intelligence Preprint Sep 2026

Explore, Execute, Evolve: A Skill Acquisition and Reuse Loop for Embodied Agents

Vision-language-action and world-action models have demonstrated impressive capabilities in robotics, yet generalization to unseen tasks remains challenging. More recently, general-purpose multimodal agents have shown great potential for zero-shot robotic task solving. However, they often incur high execution costs by...

Si-Cheng Xie, Yi-Tong Chen, Hai-Dong Cao et al. · 0 citations
Jul 2026

Scaling Behavior Foundation Model for Humanoid Robots

This work revisits the scaling recipe for BFMs and demonstrates that substantial performance gains can be achieved through the coordination of three core components: the learning paradigm of motion tracking that reformulates diverse humanoid control problems as the reproduction of integrated whole-body behaviors in the...

Weishuai Zeng, Kangning Yin, Xiaojie Niu et al. · 3 citations · ⚡1

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