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Rohan Paul· @rohanpaul_ai · X·· 3 小时前AI 评分45
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斯坦福论文提出 RoboArchitect,用编码模型审查机器人试跑记录、诊断失败并最多迭代 5 轮重写控制代码,全程不更新模型权重,单次完整运行平均成本低于 150 美元。在未见场景上平均成功率从裸策略的 9.7% 升至 43.3%,未见任务上从 12.7% 升至 40.2%。在 VLABench 上,加装控制代码的通用策略击败了在该基准上微调的同款策略,但所有测试均在仿真中完成。

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New Stanford paper shows that robot control code no longer needs hand-building for each new robot, because a coding model can diagnose failures and rewrite it automatically.

Robot policies often fail on new setups, and fixing them usually means new demonstrations and finetuning. Wrapping the policy in control code helps, but engineers write it by hand for each robot.

RoboArchitect has a coding model review recorded robot attempts, diagnose failures, and rewrite the control code over up to 5 rounds. A full run cost under $150 on average, with no weights updated.

On unseen scenes, average success rose from 9.7% for the bare policy to 43.3%, and on unseen tasks from 12.7% to 40.2%. On VLABench, the wrapped general policy beat the same policy finetuned on that benchmark, though all tests ran in simulation.

来源:Rohan Paul · x.com