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NGU, a simple adaptive sampling method that keeps generating samples for a problem until one is correct, is introduced, a simple adaptive sampling method that naturally uses fewer samples to filter out easy problems and allocates more compute to solving harder problems.
Tmax sets a new standard for terminal agent performance with a surprisingly simple RL recipe that outshines larger models.
Agentic search gets a meta-RL boost: MR-Search learns to self-reflect and adapt search strategies across episodes, significantly outperforming standard RL baselines.
