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Memory agents can boost decision-making performance by over 8% in long-horizon tasks by actively managing relevant information instead of passively retrieving it.
On-policy RL for machine learning engineering agents is now practical, thanks to a synthetic sandbox that slashes execution time by 13x while boosting performance by up to 67%.
