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Haoru Xue

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#artificial intelligence Preprint Oct 2026

Reconstruct, Practice, Go Real: Guided Self-Improvement for Embodied Agents

Building reliable robot capabilities across diverse tasks requires substantial human effort to develop and maintain skills, design rewards, and integrate perception with control. We present Reconstruct, Practice, Go Real (RPG), a framework for autonomous improvement of robot execution systems without updating model wei...

Yen-Jen Wang, Hao-Zhe Jiang, Shu-Ying Deng et al. · 0 citations
Jul 2026

GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks

Graph-as-Policy (GaP) is introduced, a multi-agent coding harness that generates directed computation graphs with perception, planning, and control nodes from a Modular Open Robot Skill Library (MORSL), and can achieve success rates that significantly outperform baselines.

Kai-Peng Chen, Shuang-Yu Xie, Letian Fu et al. · 2 citations

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