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Research & Evals · Sakana AI · University of Tokyo

Sakana AI lifts robot task success from 25% to 73%

Sakana AI and the University of Tokyo say a new test-time search method called SAIL let a vision-language model retry and revise its own robot movement plans before acting.

Sakana AI and the University of Tokyo said a new method called SAIL raised robots' success rate at finding a working trajectory from 25 percent to 73 percent in simulation. The gain came without retraining the underlying model, the companies said.

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