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Demystifying Long Chain-of-Thought Reasoning in LLMs
Summary
This paper investigates how large language models (LLMs) achieve long chain-of-thought (CoT) reasoning, which involves extended, step-by-step thought processes for complex tasks. The authors explore the roles of supervised fine-tuning (SFT) and reinforcement learning (RL) in enabling this...去小宇宙查看完整单集简介
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