--- pretty_name: MathGen license: mit language: - en task_categories: - text-to-image tags: - mathematics - text-to-image - image-generation - benchmark - script-as-a-judge - mathematical-reasoning size_categories: - n<1K configs: - config_name: default data_files: - split: clean_scene path: data/clean_scene.jsonl - split: open_scene path: data/open_scene.jsonl ---

MathGen

Revealing the Illusion of Mathematical Competence through Text-to-Image Generation

arXiv Code Project Page

## Introduction MathGen is a benchmark for evaluating mathematical correctness in text-to-image generation. It contains **420 problems** across seven core mathematical domains: counting, angle, fraction, function, plane geometry, set, and solid geometry. The benchmark includes a **350-problem Clean-Scene set** and a **70-problem Open-Scene set** with paired mathematical constraints. Each problem is evaluated with deterministic, prompt-conditioned verification scripts rather than subjective visual preference.

MathGen seven mathematical domains

## Dataset Structure This repository provides two splits: | Split | Rows | Description | | --- | ---: | --- | | `clean_scene` | 350 | Controlled mathematical diagram prompts across seven domains. | | `open_scene` | 70 | Realistic-scene prompts paired with Clean-Scene mathematical constraints. | Each row contains: | Column | Description | | --- | --- | | `id` | Stable problem id. | | `split` | `clean_scene` or `open_scene`. | | `topic` | Mathematical domain or open-scene category. | | `subtopic` | Fine-grained task type. | | `prompt` | Text-to-image prompt. | | `original_id` | Original local problem id. | | `source_topic` | Source mathematical domain. | ## Evaluation Pipeline

MathGen benchmark and evaluation pipeline

MathGen uses a Script-as-a-Judge protocol. Generated images are checked by deterministic verification scripts for numerical, geometric, topological, symbolic, and functional constraints. ## Leaderboard Main results on the **350-problem Clean-Scene set**. Accuracy is reported across seven mathematical domains, with 50 problems per domain. Best results are shown in **bold**, and second-best results are shown with underline. | Model | Counting | Angle | Fraction | Function | Plane | Set | Solid | Overall | | --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: | | SD-3-Medium | 0.0 | 0.0 | 0.0 | 0.0 | 6.0 | 0.0 | 6.0 | 1.7 | | SD-3.5-Medium | 4.0 | 0.0 | 0.0 | 0.0 | 12.0 | 2.0 | 6.0 | 3.4 | | SD-3.5-Large | 12.0 | 0.0 | 2.0 | 0.0 | 12.0 | 2.0 | 4.0 | 4.6 | | FLUX-2 | 8.0 | 2.0 | 8.0 | 2.0 | 42.0 | 8.0 | 8.0 | 11.1 | | PixArt-Sigma | 10.0 | 0.0 | 2.0 | 0.0 | 12.0 | 2.0 | 8.0 | 4.9 | | PixArt-XL-2 | 0.0 | 0.0 | 0.0 | 0.0 | 14.0 | 0.0 | 4.0 | 2.6 | | HiDream-I1 | 6.0 | 0.0 | 0.0 | 2.0 | 4.0 | 2.0 | 6.0 | 2.9 | | Qwen-Image | 22.0 | 0.0 | 8.0 | 2.0 | 24.0 | 4.0 | 6.0 | 9.4 | | Z-Image-Turbo | 8.0 | 0.0 | 8.0 | 0.0 | 16.0 | 2.0 | 14.0 | 6.9 | | Infinity-8B | 6.0 | 0.0 | 4.0 | 0.0 | 18.0 | 2.0 | 8.0 | 5.4 | | GoT-R1-7B | 8.0 | 0.0 | 0.0 | 0.0 | 16.0 | 2.0 | 2.0 | 4.0 | | BAGEL | 4.0 | 0.0 | 0.0 | 0.0 | 14.0 | 0.0 | 2.0 | 2.9 | | show-o2-1.5B | 0.0 | 0.0 | 0.0 | 4.0 | 18.0 | 0.0 | 2.0 | 3.4 | | show-o2-7B | 0.0 | 0.0 | 0.0 | 4.0 | 10.0 | 0.0 | 8.0 | 3.1 | | Janus-Pro-1B | 0.0 | 0.0 | 0.0 | 0.0 | 14.0 | 0.0 | 2.0 | 2.3 | | Janus-Pro-7B | 0.0 | 0.0 | 0.0 | 0.0 | 12.0 | 2.0 | 6.0 | 2.9 | | BLIP3o-4B | 4.0 | 0.0 | 2.0 | 0.0 | 14.0 | 2.0 | 8.0 | 4.3 | | BLIP3o-8B | 6.0 | 0.0 | 2.0 | 0.0 | 14.0 | 2.0 | 4.0 | 4.0 | | OmniGen2-7B | 4.0 | 0.0 | 2.0 | 0.0 | 12.0 | 2.0 | 8.0 | 4.0 | | FLUX-2-Pro | 22.0 | 10.0 | 20.0 | 18.0 | 54.0 | 16.0 | 20.0 | 22.9 | | FLUX-Kontext-Pro | 10.0 | 0.0 | 10.0 | 4.0 | 18.0 | 6.0 | 4.0 | 7.4 | | Seedream 3.0 | 14.0 | 0.0 | 2.0 | 0.0 | 24.0 | 6.0 | 8.0 | 7.7 | | Seedream 4.0 | 20.0 | 0.0 | 6.0 | 10.0 | 36.0 | 6.0 | 14.0 | 13.1 | | Ideogram v3 Turbo | 10.0 | 2.0 | 0.0 | 0.0 | 20.0 | 2.0 | 8.0 | 6.0 | | Nano Banana | 20.0 | 8.0 | 24.0 | 10.0 | 64.0 | 10.0 | 24.0 | 22.9 | | Nano Banana Pro | 48.0 | **54.0** | 50.0 | **70.0** | **72.0** | **42.0** | **40.0** | **53.7** | | Imagen 4 | 12.0 | 2.0 | 2.0 | 2.0 | 12.0 | 0.0 | 12.0 | 6.0 | | Imagen 4 Ultra | 20.0 | 6.0 | 16.0 | 4.0 | 42.0 | 8.0 | 16.0 | 16.0 | | GPT-Image-1 | 32.0 | 12.0 | 44.0 | 16.0 | 68.0 | 20.0 | 24.0 | 30.9 | | GPT-Image-1.5 | **56.0** | 24.0 | **54.0** | 22.0 | 70.0 | 20.0 | 28.0 | 39.1 | ## Examples

MathGen qualitative examples

## Citation ```bibtex @misc{liu2026mathgen, title={MathGen: Revealing the Illusion of Mathematical Competence through Text-to-Image Generation}, author={Liu, Ruiyao and Shen, Hui and Zhang, Ping and Hsieh, Yunta and Zhang, Yifan and Xu, Jing and Han, Qi and Li, Junchen and Lu, Jiawei and Ma, Jianing and Mo, Jiaqi and Chen, Sicheng and Zhang, Zhen and Wan, Zhongwei and Xiong, Jing and Wang, Xin and Liu, Ziyuan and Cao, Hangrui and Wong, Ngai}, year={2026}, eprint={2603.27959}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2603.27959} } ```