Experiments show that long CoT reasoning in LLMs emerges with more training compute when reward shaping is used properly, and scaling verifiable rewards from noisy data helps especially on out-of-distribution tasks.
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Demystifying Long Chain-of-Thought Reasoning in LLMs
Experiments show that long CoT reasoning in LLMs emerges with more training compute when reward shaping is used properly, and scaling verifiable rewards from noisy data helps especially on out-of-distribution tasks.