TLDR Tech / Dev
Learning to Solve Hard Problems in RL for LLMs by Never Giving Up
Standard RL mostly improves problems a model can already solve, while Never Give Up (described in this paper) reallocates compute toward harder prompts through adaptive retries, improving difficult math and coding tasks without sacrificing easier ones.
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