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Frontier multimodal agents struggle to autonomously acquire and utilize task-relevant information in unfamiliar physical environments, failing 77% of the time on a new exploration benchmark.
GRAIL reweights token advantages in reinforcement learning, leading to significant accuracy gains without the need for expensive process-level supervision.
