R-Zero
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R-Zero
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R-Zero
A framework that enables large language models to improve their reasoning abilities without requiring any human-labeled training data. The method creates a self-evolving system where two AI models work together - one generates challenging questions while the other learns to solve them, creating an autonomous learning loop that starts from scratch. R-Zero presents a novel approach to training reasoning-capable language models without requiring human-annotated data. By creating a self-evolving system where two models challenge and teach each other, the framework generates its own curriculum and learns autonomously. The method shows consistent improvements across different model sizes and architectures, with benefits that extend beyond the mathematical domain where training occurs.
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