Reproduce “Make Code as Policy Great Again: Frontier Agents Write, Call, and Evolve Robot Tools” on OpenResearch

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About this paper

Shijia Ge, Alex Zhou, Jianshu Zeng, Yexing Wan, Di Wu, Zelin Zheng, Yazhe Wang, Zhiqi Jia and 7 more

URAI lets a programming agent build timed tools that bundle multi-phase motions, while a frozen execution agent observes each result and chooses the next call. Across five RoboDojo tasks, four agents average 53.0% success through URAI versus 18.0% with native fingertip control. With identical tools, live decisions reach 56% versus 24% for written programs, but gains are task- and setup-dependent.

Summary by alphaXiv.

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