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Gödel Forest: Balancing Search Depth and Breadth for Data-Centric Recursive Self-Improvement
Recursive self-improvement (RSI) aims to achieve compounding gains by having models improve themselves. While most existing RSI systems optimize external agent harnesses or prompts around a frozen base model, data-centric RSI directly updates the model's own parameters by training on agent-generated
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