MathNet: a Global Multimodal Benchmark for Mathematical Reasoning and Retrieval
Mathematical problem solving remains a challenging test of reasoning for large language and multimodal models, yet existing benchmarks are limited in size, language coverage, and task diversity. We introduce MathNet, a high-quality, large-scale, multimodal, and multilingual dataset of Olympiad-level math problems together with a benchmark for evaluating mathematical reasoning in generative models and mathematical retrieval in embedding-based systems. MathNet spans 47 countries, 17 languages, and two decades of competitions, comprising 30,676 expert-authored problems with solutions across diverse domains. In addition to the core dataset, we construct a retrieval benchmark consisting of mat...
| Authors | Shaden Alshammari, Kevin Wen, Abrar Zainal et al. |
|---|---|
| Primary category | cs.AI |
| Published | 20 April 2026 |
| Last updated at source | 29 July 2026 |
Connected in the knowledge graph
- NP235/MathNetDataset · cited by
- archya/MathNetDataset · cited by
- anuragsbaghel/MathNetDataset · cited by
- Luowei1428/MathNetDataset · cited by
- weylmann/MathNetDataset · cited by
- Bacon935/MathNetDataset · cited by
- knowurknottty/MathNetDataset · cited by
- musumecmtcd/MathNetDataset · cited by
- ShadenA/MathNet-RetrieveDataset · cited by
- ShadenA/MathNetDataset · cited by
- introvoyz041/MathNetDataset · cited by
Models and datasets referencing this paper
- ShadenA/MathNetDataset
- NP235/MathNetDataset
- musumecmtcd/MathNetDataset
- Bacon935/MathNetDataset
- introvoyz041/MathNetDataset
- knowurknottty/MathNetDataset
- archya/MathNetDataset
- anuragsbaghel/MathNetDataset
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.