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This paper investigates whether reinforcement learning post-training can compose primitive skills into higher-level compositional strategies, using a fully observable rewrite-grammar environment. The authors find that RL reorganizes primitive competence through phased compositional mechanisms, while rejection fine-tuning plateaus due to producing many invalid shortcut-like rewrites.