Author

Jimmy Wu

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#artificial intelligence Jun 2026

ENPIRE: Agentic Robot Policy Self-Improvement in the Real World

Achieving dexterous robotic manipulation in the real world heavily relies on human supervision and algorithm engineering, which becomes a central bottleneck in the pursuit of general physical intelligence. Although emerging coding agents can generate code to automate algorithm search, their successes remain largely con...

Wenli Xiao, Jia Xie, Tonghe Zhang et al. · arXiv.org · 41 citations · ⚡3

Jul 2026

RoboTTT: Context Scaling for Robot Policies

RoboTTT, a robot model and training recipe that scale visuomotor context to 8K timesteps, three orders of magnitude beyond state-of-the-art policies, without growing inference latency, unlocks new robot capabilities: one-shot in-context imitation from human video demonstrations, on-the-fly policy improvement, robustnes...

Yunfan Jiang, Yevgen Chebo-tar, Ruijie Zheng et al. · arXiv.org · 9 citations