MathVision
MathVision is a multimodal dataset bringing together more than 3,000 mathematical problems from real competitions, with their visual context, covering 16 disciplines and 5 levels of difficulty.
Description
The dataset MathVision offers a collection of high quality visual mathematical problems, based on real competitions. Each example includes a contextual image and an associated question, covering a wide variety of disciplines and levels of difficulty.
What is this dataset for?
- Evaluate the visual mathematical reasoning skills of multimodal models
- Train models to solve complex problems using images and text
- Test performance across a broad range of mathematical disciplines
Can it be enriched or improved?
Yes, the dataset can be supplemented with additional annotations on the resolution methods or data from other competitions to broaden the diversity of problems.
🔎 In summary
🧠 Recommended for
- Multimodal AI researchers
- LMMs developers
- Math educators
🔧 Compatible tools
- Hugging Face Datasets
- PyTorch
- TensorFlow
- Multimodal frameworks
💡 Tip
Use this dataset to benchmark the mathematical visual reasoning skills of LMM models.
Frequently Asked Questions
What type of math problems are included in MathVision?
The dataset covers 16 different mathematical disciplines, with various problems in difficulty.
Does the dataset only contain images or also text?
Each example combines a contextual image with the associated math question in text.
Is this dataset suitable for training large multimodal models?
Yes, it is ideal for fine-tuning and evaluation, although the volume is limited for a full workout.
