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What is Long Chain-of-Thought in LLMs Explained about?
This study investigates the mechanics of long chain-of-thought (CoT) reasoning in large language models (LLMs), identifying key factors that enable the generation of extended reasoning sequences. The findings highlight the importance of supervised fine-tuning (SFT) and reinforcement learning (RL) in enhancing reasoning capabilities, while also addressing challenges in scaling and stabilizing long CoT generation. The research provides practical guidance for optimizing training strategies to improve long CoT
- Author
- 328697760
- Language
- EN