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SoL-Pi: Recursively Scaling Auto-Research Loops for Efficient Agent Harness

Hugging Face
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machine-learningpapers
As coding agents move from supervised code completion to unattended, around-the-clock exploration, their work expands from isolated predictions into long trajectories of reasoning, tool use, and feedback. Token efficiency therefore becomes important for scaling recursive self-improvement. We take an
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