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ReOPD turns the costly process of agent-environment interaction into a reusable offline resource, achieving faster training while preserving accuracy.
LLMs still fail to grasp research-level mathematics, with top models scoring below random chance when superficial pattern matching is removed, even with access to proof sketches.