Papers by Neil Heffernan

1 papers
DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students’ Hand-Drawn Math Images (2025.naacl-long)

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Challenge: DrawEduMath examines the ability of vision language models to handle real-world math problems, such as those encountered in classrooms and tutoring sessions.
Approach: They present DrawEduMath, an English-language dataset of 2,030 images of students’ handwritten responses to math problems.
Outcome: The proposed model can be used to evaluate teachers' QA pairs and 44,362 synthetic QAs derived from teachers' descriptions.

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