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announcement

Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning

Event Summary

arXiv:2604.18639v1 Announce Type: new Abstract: Previous LLMs-based RL studies typically follow either supervised learning with high annotation costs, or unsupervised paradigms using voting or entropy-based rewards. However, their performance remains far from satisfactory due to the substantial anno

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