The DeepSeek-R1 paper has been featured on the cover of Nature, advancing the transparency of AI.

[DeepSeek-R1 Paper Featured on Nature Cover, Advancing AI Transparency] The DeepSeek-R1 paper has been featured as a cover article in Nature, with DeepSeek founder and CEO Liang Wenfeng as the corresponding author. The research team demonstrated through experiments that the reasoning ability of large language models can be enhanced through pure reinforcement learning, reducing the workload of human input, and performing better than models trained with traditional methods in tasks such as mathematics and programming. DeepSeek-R1 has received 91.1k stars on GitHub, earning praise from developers worldwide. An assistant professor from Carnegie Mellon University remarked that it has evolved from a powerful but opaque solution seeker into a system capable of human-like dialogue. Nature's editorial article recognizes it as the first mainstream LLM published after peer review, marking a commendable step towards transparency, where peer review helps clarify the workings of LLMs, assess their effectiveness, and enhance model safety.