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On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models
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RL produces true capability gains (pass@128) only when pre-training leaves sufficient headroom and when RL data target the model's edge of competence
Reasoning gains from RL fine-tuning depend on skills already present in the base language model.
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