The
Putnam AXIOM dataset is designed for evaluating large language models (LLMs) on advanced mathematical reasoning skills. It is based on challenging problems from the Putnam Mathematical Competition. This version contains 522 original problems prepared for the ICML 2025 submission.
1from datasets import load_dataset
2
3# Load the dataset
4dataset = load_dataset("Putnam-AXIOM/putnam-axiom-dataset-ICML-2025-522")
5
6# Access each split
7full_eval = dataset["full_eval"]
8test = dataset["test"]
9val = dataset["val"]
10
11# Example usage: print the first problem from the full evaluation set
12print(full_eval[0])
1@article{putnam_axiom2025,
2 title={Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning},
3 author={Aryan Gulati and Brando Miranda and Eric Chen and Emily Xia and Kai Fronsdal and Bruno de Moraes Dumont and Sanmi Koyejo},
4 journal={39th International Conference on Machine Learning (ICML 2025)},
5 year={2025},
6 note={Preprint available at: https://openreview.net/pdf?id=YXnwlZe0yf}
7}
This dataset is licensed under the Apache 2.0.