LEARNING TO SOLVE HARD PROBLEMS IN RL FOR LLMS BY NEVER GIVING UP

Summary from the TLDR Dev newsletter

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.