EasyRL trains LLMs data-efficiently by warming up on easy labeled samples then using divide-and-conquer pseudo-labeling and progressive self-training to handle harder unlabeled data, outperforming baselines with only 10% of the labeled data.
Therefore, the only solution is(a, b) = 1 2 , 1 2
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Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning
EasyRL trains LLMs data-efficiently by warming up on easy labeled samples then using divide-and-conquer pseudo-labeling and progressive self-training to handle harder unlabeled data, outperforming baselines with only 10% of the labeled data.