MathNet is a large-scale, multilingual, multimodal mathematical reasoning dataset released in 2026 by a team from MIT in collaboration with King Abdullah University of Science and Technology and other institutions. The related research papers are as follows: MathNet: a Global Multimodal Benchmark for Mathematical Reasoning and RetrievalIt aims to evaluate and improve the capabilities of large models in Olympic-level mathematical reasoning and structured retrieval tasks, and is widely used in mathematical reasoning evaluation, RAG research, and multimodal AI training. This dataset, version v0, contains 27,817 expert-level math problems and their standard solutions. It covers official math competition problems from 58 countries and regions in 17 languages, including 5,148 illustrated problems with a total of 7,541 geometric and graphical illustrations. The dataset covers algebra, geometry, number theory, combinatorics, calculus, probability and statistics, and other Olympiad math knowledge systems. It supports three benchmark tasks: solving math problems, mathematical semantic retrieval (identifying structurally equivalent and similar problems), and retrieval enhancement problem solving.

Citation

@inproceedings{alshammari2026mathnet,
title = {MathNet: A Global Multimodal Benchmark for Mathematical
Reasoning and Retrieval},
author = {Alshammari, Shaden and Wen, Kevin and Zainal, Abrar and
Hamilton, Mark and Safaei, Navid and Albarakati, Sultan and
Freeman, William T. and Torralba, Antonio},
booktitle = {International Conference on Learning Representations},
year = {2026},
url = {https://mathnet.mit.edu}
}