This research paper introduces DeepSeek-R1, a large language model (LLM) enhanced for reasoning capabilities using reinforcement learning (RL). A preliminary model, DeepSeek-R1-Zero, utilised RL without initial supervised fine-tuning, showcasing inherent reasoning abilities despite readability issues. DeepSeek-R1 addresses these limitations through multi-stage training incorporating cold-start data, achieving performance comparable to OpenAI's o1-1217. Furthermore, the study demonstrates the successful distillation of DeepSeek-R1's reasoning capabilities into smaller, more efficient LLMs. The researchers open-source their models and data to foster further research in this area.

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