MathWriting: A Dataset For Handwritten Mathematical Expression Recognition

Recognition of handwritten mathematical expressions allows to transfer scientific notes into their digital form. It facilitates the sharing, searching, and preservation of scientific information. We introduce MathWriting, the largest online handwritten mathematical expression dataset to date. It consists of 230k human-written samples and an additional 400k synthetic ones. This dataset can also be used in its rendered form for offline HME recognition. One MathWriting sample consists of a formula written on a touch screen and a corresponding LaTeX expression. We also provide a normalized version of LaTeX expression to simplify the recognition task and enhance the result quality. We provide baseline performance of standard models like OCR and CTC Transformer as well as Vision-Language Models like PaLI on the dataset. The dataset together with an example colab is accessible on Github.

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Publication Details

Published
2025-08-03
DOI
https://doi.org/10.1145/3711896.3737436
Citations
3
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
3.83
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article

MathWriting: A Dataset For Handwritten Mathematical Expression Recognition

P. Gervais, Andrii Maksai, Anastasiia Fadeeva
3 citations
Handwritten Text Recognition Techniques
3.83
article

MathWriting: A Dataset For Handwritten Mathematical Expression Recognition

P. Gervais, Andrii Maksai, Anastasiia Fadeeva
article en
3 citations

Abstract

Recognition of handwritten mathematical expressions allows to transfer scientific notes into their digital form. It facilitates the sharing, searching, and preservation of scientific information. We introduce MathWriting, the largest online handwritten mathematical expression dataset to date. It consists of 230k human-written samples and an additional 400k synthetic ones. This dataset can also be used in its rendered form for offline HME recognition. One MathWriting sample consists of a formula written on a touch screen and a corresponding LaTeX expression. We also provide a normalized version of LaTeX expression to simplify the recognition task and enhance the result quality. We provide baseline performance of standard models like OCR and CTC Transformer as well as Vision-Language Models like PaLI on the dataset. The dataset together with an example colab is accessible on Github.

University of Bern (CH), Google (Switzerland) (CH)
Quality Education
Openalex Percentile: Top 6%
Handwritten Text Recognition Techniques
3.83
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MathWriting: A Dataset For Handwritten Mathematical Expression Recognition — P. Gervais, Andrii Maksai, et al. · (2025) | TGRS Research Map | TGRS