{"url":"/dataset/beyondx","name":"BeyondX","full_name":null,"description_markdown":"# Dataset Card for BeyondX\r\n\r\n- [Dataset Description](https://huggingface.co/datasets/Johnson0213/BeyondX#dataset-description)\r\n- [Paper Information](https://huggingface.co/datasets/Johnson0213/BeyondX#paper-information)\r\n- [Dataset Usage](https://huggingface.co/datasets/Johnson0213/BeyondX#dataset-usage)\r\n  - [Data Construction](https://huggingface.co/datasets/Johnson0213/BeyondX#data-construction)\r\n  - [Formulate-and-Solve](https://huggingface.co/datasets/Johnson0213/BeyondX#formulate-and-solve)\r\n- [License](https://huggingface.co/datasets/Johnson0213/BeyondX#license)\r\n- [Citation](https://huggingface.co/datasets/Johnson0213/BeyondX#citation)\r\n\r\n## Dataset Description\r\n\r\n**BeyondX** is a novel algebra reasoning benchmark within multi-unknown, which addresses the limitation that problems with at most two unknowns dominate existing math datasets. In total, **BeyondX** includes 464 examples generated from **2 different source datasets**.\r\n\r\n## Paper Information\r\n- Project Page: https://johnsonkao0213.github.io/Formulate_and_Solve/\r\n- Paper: https://arxiv.org/abs/2407.05134\r\n- Code: https://github.com/johnsonkao0213/Formulate_and_Solve\r\n- Visualization: https://johnsonkao0213.github.io/Formulate_and_Solve/#visualization\r\n- Leaderboard: https://johnsonkao0213.github.io/Formulate_and_Solve/#leaderboard\r\n\r\n## Dataset Usage\r\n\r\n### Data Construction\r\n\r\nThe **BeyondX** dataset is derived from two collected datasets: [ALG514](https://paperswithcode.com/dataset/alg514) and [DRAW-1K](https://paperswithcode.com/dataset/draw-1k). To efficiently generate a large corpus of multi-unknown problems, we developed a novel pipeline that automatically expands existing problems to *N* unknowns, please refer to our GitHub repository and Paper for details [here](https://github.com/johnsonkao0213/Formulate_and_Solve).\r\n\r\n### Formulate-and-Solve\r\n\r\n🔔 To evaluate our proposed SoTA prompting method **Formulate-and-Solve** on **BeyondX**, please refer to our GitHub repository and Paper for details [here](https://github.com/johnsonkao0213/Formulate_and_Solve).\r\n\r\n## License\r\n\r\nThe new contributions to our dataset are distributed under the [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) license.\r\n\r\nThe copyright of the questions belongs to the original authors, and the source of every original question can be found in the `source` field. Alongside this license, the following conditions apply:\r\n\r\n- **Purpose:** The dataset was primarily designed as a test set.\r\n- **Commercial Use:** The dataset can be used commercially as a test set, but using it as a training set is prohibited. By accessing or using this dataset, you acknowledge and agree to abide by these terms in conjunction with the [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) license.\r\n\r\n## Citation\r\n\r\n```latex\r\n@misc{kao2024solvingxbeyondlarge,\r\n      title={Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns?}, \r\n      author={Kuei-Chun Kao and Ruochen Wang and Cho-Jui Hsieh},\r\n      year={2024},\r\n      eprint={2407.05134},\r\n      archivePrefix={arXiv},\r\n      primaryClass={cs.AI},\r\n      url={https://arxiv.org/abs/2407.05134}, \r\n}\r\n```","description_withheld":null,"homepage":"https://huggingface.co/datasets/Johnson0213/BeyondX","introduced_date":"2024-07-06","introduced_date_note":null,"introduced_by":{"paper":"/paper/solving-for-x-and-beyond-can-large-language","title":"Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns?","first_author":"Kuei-Chun Kao","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["BeyondX"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}