| --- |
| license: cc |
| task_categories: |
| - question-answering |
| language: |
| - en |
| tags: |
| - math |
| pretty_name: Can Vision-Language Models Solve Visual Math Equations? |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # Visual Equation Solving Benchmark |
|
|
| This repository contains the dataset introduced in the paper: |
|
|
| **Can Vision-Language Models Solve Visual Math Equations?** which is currently accepted in EMNLP 2025 (Main) |
|
|
| > Despite strong performance in vision and language understanding, Vision-Language Models (VLMs) struggle on tasks requiring integrated perception and symbolic reasoning. This benchmark evaluates VLMs on **visual equation solving**, where systems of linear equations are represented using **object icons** as variables and **icon repetition** as coefficients. |
|
|
| --- |
|
|
| ## 📖 Overview |
|
|
| The **Visual Equation Solving Benchmark** tests whether VLMs can: |
| 1. **Recognize variables** represented as object icons. |
| 2. **Count coefficients** by inferring from repeated instances of icons. |
| 3. **Integrate recognition with symbolic reasoning** to solve equations. |
|
|
| We provide multiple settings: |
| - **Symbolic equations** (textual form, rendered as images). |
| - **Visual-symbolic equations** (icons for variables, numeric text for coefficients). |
| - **Fully visual equations** (both variables and coefficients represented visually). |
|
|
| --- |
|
|
| Example: |
| ``` |
| |
| 🍎🍎🍎 + 🍌🍌 = 10 |
| 🍎 + 🍌🍌🍌🍌🍌 = 15 |
| |
| ``` |
|
|
| --- |
|
|
| ## 📂 Dataset Structure |
|
|
|
|
| There are 2 variants of the dataset based on number of variables used - |
| 2 variables and 3 variables which can be found in the respective zip files. |
| Once you extract any of them you will see the following tree - |
| ``` |
| ├── char_only |
| │ └── metadata.csv |
| │ └── *.png |
| ├── counting |
| │ └── metadata.csv |
| │ └── *.png |
| ├── icon_only |
| │ └── metadata.csv |
| │ └── *.png |
| ├── icon_partial |
| │ └── metadata.csv |
| │ └── *.png |
| └── [two/three]-vars.txt |
| ``` |
| The char_only, icon_only, icon_partial, counting points to the |
| symbolic, visual, visual-symbolic and counting datasets mentioned in the paper |
| respectively. Each of them consist of the following metadata - |
| 1. file_path to corresponding image |
| 2. solution to variable |
| 3. mapping to symbolic variable (in case of visual, visual-symbolic, counting dataset) |
|
|
| The base equations which are used to create the same are attached in the respective .txt file in the root level directory. |
| |
| --- |
|
|
| ## 📜 License |
|
|
| This dataset is released under the **CC BY 4.0 License**. |
| You are free to share, adapt, and build upon the data with attribution. |
|
|
| --- |
|
|
| ## 📚 Citation |
|
|
| If you use this dataset, please cite: |
|
|
| ```bibtex |
| @inproceedings{anonymous2025vlm-math, |
| title = {Can Vision-Language Models Solve Visual Math Equations?}, |
| author = {Anonymous}, |
| booktitle = {ACL (under review)}, |
| year = {2025} |
| } |
| ``` |