RL Can Learn Reusable Skills
heghbalz · x · 2026-07-10
This snippet continues the discussion on the effects of RL under final answer rewards: even without intermediate step supervision, RL can solve held-out problems that the base model essentially cannot crack.
Explaining the mechanism, the author concludes that RL first strengthens raw skills, then combines them into more complex processes, ultimately forming a stable, repeatedly callable "toolbox."
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