✨Data Repetition Beats Data Scaling in Long-CoT Supervised Fine-Tuning

📝 Summary:
Training reasoning language models benefits from data repetition. For a fixed update budget, more epochs on smaller datasets beat single-pass training on larger datasets. Token accuracy signals optimal training duration.

🔹 Publication Date: Published on Feb 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11149
• PDF: https://arxiv.org/pdf/2602.11149
• Github: https://github.com/dkopi/data-repetition

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