The study challenges conventional beliefs about LLM training by showing that reasoning ability is largely determined by structural consistency rather than the correctness of content. Through experiments using long chain-of-thought (Long CoT) training, the researchers fine-tuned the Qwen2.5-32B-Instruct model with only 17,000 structured reasoning samples. The results were striking: the model demonstrated significant improvements in complex math and coding tasks, outperforming proprietary models like OpenAI’s o1-preview in key benchmarks.
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