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OpenAI's o1 and Journey Learning
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This paper details the authors' research journey to replicate OpenAI's "O1" language model, which is designed to solve complex reasoning tasks. The researchers document their process with detailed insights, hypotheses, and challenges encountered. They present a novel paradigm called "Journey Learning" that enables models to learn the complete exploration process, including trial and error, reflection, and backtracking, which they argue outperforms traditional "shortcut learning" methods. The authors also propose a multi-step evaluation approach that utilizes reasoning trees, reward models, and a human-AI collaborative annotation pipeline to generate high-quality long-form reasoning data.
Read more: https://github.com/GAIR-NLP/O1-Journey/blob/main/resource/report.pdf
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