mlsanityData to 14 Oct 2026

GeoUni: A Unified Model for Generating Geometry Diagrams, Problems and Problem Solutions

arXiv 2504.10146 ↗First posted 14 Apr 2025cs.LG cs.AIcited by 11

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 23 of its 47 references that are in the map. First posted on arXiv 14 Apr 2025.

Builds on

23 of 47 references.

References · 23

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  2. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
  3. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  4. 2023Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyondcited by 2,224
  5. 2024Chameleon: Mixed-Modal Early-Fusion Foundation Modelscited by 927
  6. 2025Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scalingcited by 812
  7. 2025Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAscited by 521
  8. 2022Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Taskscited by 421
  9. 2021Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoningcited by 383
  10. 2024SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generationcited by 331
  11. 2024LoRA Learns Less and Forgets Lesscited by 328
  12. 2021GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoningcited by 228
11 more
  1. 2023Making LLaMA SEE and Draw with SEED Tokenizercited by 185
  2. 2024Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generationcited by 155
  3. 2025UniTok: A Unified Tokenizer for Visual Generation and Understandingcited by 153
  4. 2023A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagramcited by 56
  5. 2025QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generationcited by 45
  6. 2024GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generationcited by 32
  7. 2022OCR-VQGAN: Taming Text-within-Image Generationcited by 31
  8. 2023FormalGeo: An Extensible Formalized Framework for Olympiad Geometric Problem Solvingcited by 27
  9. 2024GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-trainingcited by 23
  10. 2024Diagram Formalization Enhanced Multi-Modal Geometry Problem Solvercited by 11
  11. 2025MagicGeo: Training-Free Text-Guided Geometric Diagram Generationcited by 11

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 6.

11 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025GeoThought: A Dataset for Enhancing Mathematical Geometry Reasoning in Vision-Language Models
  2. 2023GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoning
  3. 2025GeoRef: Referring Expressions in Geometry via Task Formulation, Synthetic Supervision, and Reinforced MLLM-based Solutions
  4. 2026GeoChallenge: A Multi-Answer Multiple-Choice Benchmark for Geometric Reasoning with Diagrams
  5. 2024GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models
  6. 2024Learning to Solve Geometry Problems via Simulating Human Dual-Reasoning Process
  7. 2024Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems with Meta In-Context Learning
  8. 2025GeoFM: Enhancing Geometric Reasoning of MLLMs via Synthetic Data Generation through Formal Language