{"url":"/dataset/mathqa","name":"MathQA","full_name":null,"description_markdown":"MathQA significantly enhances the AQuA dataset with fully-specified operational programs. \r\n\r\nSource: [MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms](/paper/mathqa-towards-interpretable-math-word)","description_withheld":null,"homepage":"https://math-qa.github.io/math-QA/","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/mathqa-towards-interpretable-math-word","title":"MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms","first_author":"Aida Amini","url":null},"license":{"name":"Custom","url":"https://math-qa.github.io/math-QA/"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"},{"name":"Math Word Problem Solving","url":"/task/math-word-problem-solving","datasets_with_task":"/datasets/task/math-word-problem-solving"},{"name":"Data Augmentation","url":"/task/data-augmentation","datasets_with_task":"/datasets/task/data-augmentation"}],"languages":[],"variants":["MathQA","math_qa"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/allenai/math_qa","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/math_qa","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/tensorflow/datasets","url":"https://www.tensorflow.org/datasets/catalog/math_qa","frameworks":["tf","pytorch","jax"]}],"num_papers_in_archive":159,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/math-word-problem-solving-on-mathqa","task":"Math Word Problem Solving","dataset_variant":"MathQA","rows":5,"metrics":["Answer Accuracy"],"first_row_in_archive_order":{"model":"ELASTIC (RoBERTa-large)","paper":"/paper/elastic-numerical-reasoning-with-adaptive","metrics":{"Answer Accuracy":"83.00"},"code_links":[{"title":"neurasearch/neurips-2022-submission-3358","url":"https://github.com/neurasearch/neurips-2022-submission-3358"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/an-expression-tree-decoding-strategy-for","title":"An Expression Tree Decoding Strategy for Mathematical Equation Generation","date":"2023-10-14","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multi-view-reasoning-consistent-contrastive","title":"Multi-View Reasoning: Consistent Contrastive Learning for Math Word Problem","date":"2022-10-21","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":13,"samples_ran":1,"samples_unverified":12,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/elastic-numerical-reasoning-with-adaptive","title":"ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler","date":"2022-10-18","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-to-reason-deductively-math-word","title":"Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction","date":"2022-03-19","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/mwp-bert-a-strong-baseline-for-math-word","title":"MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem Solving","date":"2021-07-28","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":2,"samples_unverified":2,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":22,"samples_ran":6,"samples_unverified":16,"pointer_only_for_licence":7,"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."}