What is XBai o4
XBai o4 is an open-source large language model trained based on the "Reflective Generation Form", combining long CoT reinforcement learning and process reward learning, demonstrating outstanding performance in complex reasoning capabilities, and in medium mode has surpassedOpenAI-o3-mini. XBai o4 is based on a shared backbone network of PRMs and policy models, significantly reducing reasoning costs. The model performs excellently on multiple benchmarks, such as AIME24, LiveCodeBench v5, etc. The model supports single-node and multi-node training, and provides detailed installation and evaluation processes, offering developers powerful tools and flexible usage.
XBai o4's main features
- Complex reasoning capability: capable of handling multi-step complex logical reasoning and mathematical problems, generating high-quality reasoning traces.
- Efficient reasoning: based on a shared backbone network of PRMs and policy models, significantly reducing reasoning costs and improving reasoning efficiency.
- Multilingual support: supports multiple languages, can process and generate high-quality text content, suitable for various natural language processing tasks.
- Flexible training and deployment: provides detailed training and deployment guides, supports single-node and multi-node training, making it convenient for developers to train models according to hardware conditions.
- Multi-task learning: combines multiple tasks for training, including language modeling, mathematical reasoning, and logical reasoning, improving the model's generalization ability and adaptability.
XBai o4's technical principles
- Reflective Generation Form: XBai o4 is trained with the "Reflective Generation Form", combining "long CoT (Chain of Thought) reinforcement learning" and "process reward learning", enabling the model to simultaneously achieve deep reasoning and selection of high-quality reasoning traces.
- Process Reward Learning: Process reward learning is a reinforcement learning method that, based on the performance of a reward model during the reasoning process, enables the model to better learn the intermediate steps in the reasoning process and improve overall reasoning ability. XBai-o4 is based on a shared backbone network of PRMs and policy models, further optimizing the reasoning process and reducing computational costs.
- Multi-task learning: During training, the model combines multiple tasks, including language modeling, mathematical reasoning, logical reasoning, etc. The multi-task learning method enables the model to better adapt to different application scenarios and improve its generalization ability. Based on evaluation across multiple benchmarks, it demonstrates excellent performance on different tasks.
- Efficient reasoning architecture: The model uses an efficient reasoning architecture, optimizing the model's structure and computation process to improve reasoning speed. For example, the model supports multiple reasoning modes, allowing users to choose the appropriate mode according to specific needs, balancing reasoning speed and accuracy. The model provides detailed reasoning processes and evaluation methods, making it convenient for users to optimize and adjust in practical applications.
XBai o4's project address
- GitHub repository：https://github.com/MetaStone-AI/XBai-o4/
- HuggingFace model library：https://hf-mirror.com/MetaStoneTec/XBai-o4
XBai o4's application scenarios
- Education field: assists teaching, provides students with solutions to complex mathematical and logical problems, helping users better understand the problem-solving process.
- Scientific research assistance: in scientific research work, used for literature reviews, generation of experimental design ideas, and reasoning analysis of complex scientific problems.
- Programming assistance: Can provide developers with suggestions for code generation, logical reasoning, and troubleshooting, improving programming efficiency and code quality.
- Content Creation: In copywriting, creative writing, and other areas, quickly generate high-quality text content and inspire creators' inspiration.
- Intelligent Customer Service: Provide users with accurate answers and solutions, improving customer service efficiency and user experience.