DeepSeek Launches CODEI/O: Enhancing Large Model Inference with Thought Chains
DeepSeek's CODEI/O dataset enhances model reasoning by transforming code into natural language thought chains, improving performance across various reasoning tasks.
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Training large models with code can also enhance reasoning abilities in other areas.
The DeepSeek team's latest research utilizes over 3 million instances to transform code into thought processes. They created a dataset called CODEI/O to train models such as Qwen and Llama.
The results showed a significant improvement in model performance across various types of reasoning tasks, including demonstrating strong transferability in non-code reasoning tasks.
The research team believes that code contains implicit thought processes for various scenarios and aims to "extract" these processes to train reasoning models.
