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- ---
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- dataset_info:
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- features:
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- - name: year
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- dtype: string
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- - name: id
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- dtype: string
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- - name: problem
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- dtype: string
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- - name: solution
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- dtype: string
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- - name: answer_type
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- dtype: string
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- - name: source
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- dtype: string
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- - name: type
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- dtype: string
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- - name: original_problem
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- dtype: string
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- - name: original_solution
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- dtype: string
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- - name: variation
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- dtype: int64
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- splits:
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- - name: full_eval
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- num_examples: 522
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- - name: test
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- num_examples: 372
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- - name: val
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- num_examples: 150
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- download_size: 560892
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- dataset_size: 1184885
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- configs:
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- - config_name: default
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- extra_gated_prompt: 'By requesting access to this dataset, you agree to cite the following
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- works in any publications or projects that utilize this data:
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-
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- - Putnam-AXIOM dataset: @article{putnam_axiom2025, title={Putnam-AXIOM: A Functional
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- and Static Benchmark for Measuring Higher Level Mathematical Reasoning}, author={Aryan
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- Gulati and Brando Miranda and Eric Chen and Emily Xia and Kai Fronsdal and Bruno
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- de Moraes Dumont and Sanmi Koyejo}, journal={39th International Conference on Machine Learning (ICML 2025)}, year={2025},
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- note={Preprint available at: https://openreview.net/pdf?id=YXnwlZe0yf}} '
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- ---
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-
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- # Putnam AXIOM Dataset (ICML 2025 Version)
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-
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- **Note: for questions, feedback, bugs, etc. please [open a Huggingface discussion here](https://huggingface.co/datasets/Putnam-AXIOM/putnam-axiom-dataset-ICML-2025-522/discussions).**
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-
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- ## Dataset Summary
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-
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- The [**Putnam AXIOM**](https://openreview.net/pdf?id=YXnwlZe0yf) 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.
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-
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- This dataset includes:
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- - **Full Evaluation Set (522 problems)**: Complete set of problems
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- - **Test Set (372 problems)**: Set used for testing
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- - **Validation Set (150 problems)**: Set used for validation/development
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-
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- Each problem includes:
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- - Problem statement
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- - Solution
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- - Original problem (where applicable)
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- - Answer type (e.g., numerical, proof)
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- - Source and type of problem (e.g., Algebra, Calculus, Geometry)
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- - Year (extracted from problem ID)
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-
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- ## Supported Tasks and Leaderboards
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-
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- - **Mathematical Reasoning**: Evaluate mathematical reasoning and problem-solving skills.
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- - **Language Model Benchmarking**: Use this dataset to benchmark performance of language models on advanced mathematical questions.
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-
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- ## Languages
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-
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- The dataset is presented in **English**.
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-
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- ## Dataset Structure
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-
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- ### Data Fields
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-
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- - **year**: The year of the competition (extracted from the problem ID).
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- - **id**: Unique identifier for each problem.
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- - **problem**: The problem statement.
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- - **solution**: The solution or explanation for the problem.
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- - **answer_type**: The expected type of answer (e.g., numerical, proof).
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- - **source**: The origin of the problem (Putnam).
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- - **type**: A description of the problem's mathematical topic (e.g., "Algebra Geometry").
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- - **original_problem**: Original form of the problem, where applicable.
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- - **original_solution**: Original solution to the problem, where applicable.
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- - **variation**: Flag for variations (0 for all problems in this dataset as these are not variations).
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-
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- ### Splits
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-
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- | Split | Description | Number of Problems |
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- |-------------|----------------------------------------|--------------------|
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- | `full_eval` | Complete set of 522 problems | 522 |
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- | `test` | Test split | 372 |
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- | `val` | Validation/development split | 150 |
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-
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- ## Dataset Usage
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-
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- ```python
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- from datasets import load_dataset
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-
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- # Load the dataset
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- dataset = load_dataset("Putnam-AXIOM/putnam-axiom-dataset-ICML-2025-522")
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-
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- # Access each split
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- full_eval = dataset["full_eval"]
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- test = dataset["test"]
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- val = dataset["val"]
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-
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- # Example usage: print the first problem from the full evaluation set
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- print(full_eval[0])
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- ```
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-
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- ## Citation
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- If you use this dataset, please cite it as follows:
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-
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- ```bibtex
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- @article{putnam_axiom2025,
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- title={Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning},
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- author={Aryan Gulati and Brando Miranda and Eric Chen and Emily Xia and Kai Fronsdal and Bruno de Moraes Dumont and Sanmi Koyejo},
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- journal={39th International Conference on Machine Learning (ICML 2025)},
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- year={2025},
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- note={Preprint available at: https://openreview.net/pdf?id=YXnwlZe0yf}
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- }
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- ```
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-
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- ## License
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-
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- This dataset is licensed under the Apache 2.0.
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-
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- Last updated: May 22, 2024