GeoUni统一生成几何题、图和解法，1.5亿参数媲美6710亿参数大模型。
GeoUni: A Unified Model for Generating Geometry Diagrams, Problems and Problem Solutions
- 用统一框架实现几何题、图、解法的端到端生成。
- 1.5B参数模型在几何推理上接近671B参数模型表现。
- 唯一能根据知识点生成匹配图文的几何生成模型。
我们提出GeoUni，首个统一的几何专家模型，可在单一框架内生成几何问题、解法及对应图形，支持个性化题目创建。传统方法将解题与绘图视为独立任务，缺乏有效整合。而几何能力的真正掌握需流畅衔接解题、可视化与命题设计。实验表明，仅含1.5亿参数的GeoUni，在几何推理任务中表现可比肩拥有6710亿参数的DeepSeek-R1。GeoUni在生成精准几何图形方面优于文本转图像模型及统一模型（包括GPT-4o图像生成）。最重要的是，它是唯一能基于特定知识点成功生成匹配图文的几何问题的模型，能力远超现有模型。
原文摘要 · Abstract (English)
We propose GeoUni, the first unified geometry expert model capable of generating problem solutions and diagrams within a single framework in a way that enables the creation of unique and individualized geometry problems. Traditionally, solving geometry problems and generating diagrams have been treated as separate tasks in machine learning, with no models successfully integrating both to support problem creation. However, we believe that mastery in geometry requires frictionless integration of all of these skills, from solving problems to visualizing geometric relationships, and finally, crafting tailored problems. Our extensive experiments demonstrate that GeoUni, with only 1.5B parameters, achieves performance comparable to larger models such as DeepSeek-R1 with 671B parameters in geometric reasoning tasks. GeoUni also excels in generating precise geometric diagrams, surpassing both text-to-image models and unified models, including the GPT-4o image generation. Most importantly, GeoUni is the only model capable of successfully generating textual problems with matching diagrams based on specific knowledge points, thus offering a wider range of capabilities that extend beyond current models.
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