Introducing MathQA -- A Math-Aware Question Answering System
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Abstract (arXiv)
We present an open source math-aware Question Answering System based on Ask Platypus. Our system returns as a single mathematical formula for a natural language question in English or Hindi. This formulae originate from the knowledge-base Wikidata. We translate these formulae to computable data by integrating the calculation engine sympy into our system. This way, users can enter numeric values for the variables occurring in the formula. Moreover, the system loads numeric values for constants occurring in the formula from Wikidata. In a user study, our system outperformed a commercial computational mathematical knowledge engine by 13%. However, the performance of our system heavily depends on the size and quality of the formula data available in Wikidata. Since only a few items in Wikidata contained formulae when we started the project, we facilitated the import process by suggesting formula edits to Wikidata editors. With the simple heuristic that the first formula is significant for the article, 80% of the suggestions were correct.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Jun 2019.
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Citing papers per year: 2022: 2; 2023: 4; 2024: 2.
8 papers.
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- 2022Why is constrained neural language generation particularly challenging?cited by 19
- 2024LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Surveycited by 12
- 2023GLUECons: A Generic Benchmark for Learning Under Constraintscited by 9
- 2023Divide & Conquer for Entailment-aware Multi-hop Evidence Retrievalcited by 3
- 2023Discovery and Recognition of Formula Concepts using Machine Learningcited by 1
- 2023Perturbation-based Active Learning for Question Answeringcited by 0
- 2024VcLLM: Video Codecs are Secretly Tensor Codecscited by 0
- 2024VcLLM: Video Codecs are Secretly Tensor Codecs29 Jun 2024
- 2024LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Survey22 Feb 2024
- 2023Divide & Conquer for Entailment-aware Multi-hop Evidence Retrieval5 Nov 2023
- 2023Perturbation-based Active Learning for Question Answering4 Nov 2023
- 2023Discovery and Recognition of Formula Concepts using Machine Learning3 Mar 2023
- 2023GLUECons: A Generic Benchmark for Learning Under Constraints16 Feb 2023
- 2022Multi-lingual Evaluation of Code Generation Models26 Oct 2022
- 2022Why is constrained neural language generation particularly challenging?11 Jun 2022