A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers (2020.acl-main)
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| Challenge: | Existing MWP corpora are limited in language patterns and problem types . a new corpus of 2,305 MWps is proposed that is more diverse in terms of lexicon usage . |
| Approach: | They propose to use ASDiv to measure lexicon usage diversity of a given MWP corpus. |
| Outcome: | The proposed corpus covers more problem types and text patterns than existing corpora and reflects the true capability of solvers more faithfully. |
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| Challenge: | Existing studies lack diversity in problem types, lexical usage patterns, languages, and intermediate solution forms for the math word problem. |
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| Challenge: | Existing methods for solving math word problem (MWP) use shortcut learning to train solvers based on samples with a single question. |
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| Challenge: | Experiments show that even quite powerful LLMs are still challenged by MWPs. |
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Are NLP Models really able to Solve Simple Math Word Problems? (2021.naacl-main)
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| Challenge: | Existing solvers for math word problems often achieve high performance on benchmark datasets . existing models rely on shallow heuristics to achieve high accuracy . |
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Math Word Problem Solving by Generating Linguistic Variants of Problem Statements (2023.acl-srw)
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Syed Rifat Raiyan, Md Nafis Faiyaz, Shah Md. Jawad Kabir, Mohsinul Kabir, Hasan Mahmud, Md Kamrul Hasan
| Challenge: | Existing models for solving Math Word Problems depend on shallow heuristics and spurious correlations to derive the solution expressions. |
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ArMATH: a Dataset for Solving Arabic Math Word Problems (2022.lrec-1)
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| Challenge: | This paper is the first to use deep learning methods to solve Arabic MWPs . it is also the first study to use transfer learning to solve MWp across different languages . |
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The ACQDIV Corpus Database and Aggregation Pipeline (2020.lrec-1)
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| Challenge: | ACQDIV corpus database and aggregation pipeline aims to identify universal cognitive processes that allow children to acquire any language. |
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| Challenge: | Until recently, language descriptions were available in paper form only, with indexes as the only search aid. |
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TMATH A Dataset for Evaluating Large Language Models in Generating Educational Hints for Math Word Problems (2025.coling-main)
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| Challenge: | Large Language Models (LLMs) are increasingly being applied in education, showing significant potential in personalized instruction, student feedback, and intelligent tutoring systems (ITSs). |
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EDUMATH: Generating Standards-aligned Educational Math Word Problems (2026.acl-long)
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Bryan R Christ, Penelope Molitz, Beau LeBlond, Zachary Gottesman, Jonathan Kropko, Thomas Hartvigsen
| Challenge: | Math word problems (MWPs) are critical elements of K-12 math education and can be customized to students' interests and ability levels. |
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