AI Research
Supervised Fine-Tuning for Reasoning Large Language Models: A Survey
A survey examines how long chain-of-thought data supports reasoning in large language models.
Large reasoning models have recently demonstrated remarkable capabilities in solving complex tasks, where supervised fine-tuning (SFT) on long chain-of-thought data serves as a crucial foundation for eliciting and enhancing their reasoning abilities.
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ArXiv CS.CL
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ArXiv CS.CL
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Supervised fine-tuning on long chain-of-thought data is presented as a key foundation for developing reasoning abilities in large language models. Understanding this role matters as researchers seek to improve performance on complex tasks.
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