Generating Pedagogically Meaningful Visuals for Math Word Problems: A New Benchmark and Analysis of Text-to-Image Models
Findings of the Association for Computational Linguistics: ACL 2025, 2025
Math2Visual generates instructional illustrations for math word problems and provides a benchmark for evaluating educational image generation.
Recommended citation: Junling Wang, Anna Rutkiewicz, April Yi Wang, Mrinmaya Sachan. (2025). "Generating Pedagogically Meaningful Visuals for Math Word Problems: A New Benchmark and Analysis of Text-to-Image Models." Findings of the Association for Computational Linguistics: ACL 2025. https://aclanthology.org/2025.findings-acl.586/