# Reasoning Models

AlphaOne (α1) is a general framework for regulating the thinking progress of large reasoning models (LRMs) during testing. By introducing α moments and dynamically scheduling slow transitions in thinking stages, α1 achieves flexible regulation from slow to fast reasoning. This method unifies and extends existing monotonic scaling approaches, optimizing reasoning capabilities and computational efficiency. The product is applicable for researchers and developers who need to handle complex reasoning tasks.

Open Thoughts is a project led by Bespoke Labs and the DataComp community, aimed at curating high-quality open-source reasoning datasets for training advanced small models. The project brings together researchers and engineers from various universities and research institutions, including Stanford University, the University of California, Berkeley, and the University of Washington, dedicated to promoting the development of reasoning models through high-quality datasets. The project is established in response to the growing demand for applications of reasoning models in fields such as mathematics and code reasoning, where high-quality datasets are critical for improving model performance. Currently free to access, the project primarily targets researchers, developers, and professionals interested in reasoning models, with its open-source datasets and tools serving as a significant resource for advancing AI education and research.

Dolphin R1 is a dataset created by the Cognitive Computations team, aimed at training reasoning models similar to the DeepSeek-R1 Distill model. The dataset comprises 300,000 reasoning samples from DeepSeek-R1, 300,000 reasoning samples from Gemini 2.0 flash thinking, and 200,000 Dolphin chat samples. This combination provides researchers and developers with abundant training resources, enhancing model reasoning and dialogue capabilities. The creation of this dataset was supported by sponsors such as Dria, Chutes, and Crusoe Cloud, who contributed computational resources and funding. The release of the Dolphin R1 dataset offers a critical foundation for research and development in the field of natural language processing, fostering the advancement of related technologies.