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  ### Dataset Description
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  - **Curated by:** Roman
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- - **Funded by Roman:** [No funding needed]
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  - **Shared by Roman:** Also made by Roman
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  - **Language(s) (NLP):** English
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  - **License:** Common Creatives Attribution Share Alike 4.0
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  ### Dataset Sources [optional]
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- - **Repository:** [https://huggingface.co/datasets/DataMuncher-Labs/LaTeXOCR]
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  - **I don't write papers or demos**
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  ## Uses
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  <!-- This section describes suitable use cases for the dataset. -->
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- [Pre/Post training corpra for visual understanding of mathematics.]
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  ### Out-of-Scope Use
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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- [The dataset uses the format of]
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  problem_latex|solution_latex|problem_english
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  <!-- Motivation for the creation of this dataset. -->
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- [I thought there was simply a lack of mathematical OCR datasets]
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  ### Source Data
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  <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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- [Data was sourced from python...]
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  **Its synthetic data**
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  <!--*I don't upload webscraped data cause im afraid i could get copyrighted ;-;*-->
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@@ -89,23 +89,23 @@ problem_latex|solution_latex|problem_english
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  <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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- [Roman]
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- [Ai assisted in making some parts of the script (sympy is hard)]
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  #### Personal and Sensitive Information
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  <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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- [No PII or Sensitive information]
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  *Also why I make synthtic data*
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [Doesnt cover all equation types]
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- [Doesnt cover all numbers possible]
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- [There are aready similar datasets]
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  ### Recommendations
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  **BibTeX:**
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- @dataset{datamuncher_latexocr_2026,
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  author = {DataMuncher-Labs},
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- title = {LaTeXOCR},
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  year = {2026},
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  publisher = {Hugging Face},
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- url = {https://huggingface.co/datasets/DataMuncher-Labs/LaTeXOCR},
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- note = {Synthetic LaTeX equation OCR dataset}
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  }
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  **APA:**
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- **DataMuncher-Labs. (2026). LaTeXOCR [Dataset]. Hugging Face. https://huggingface.co/datasets/DataMuncher-Labs/LaTeXOCR**
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  ## Dataset Card Authors
 
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  ### Dataset Description
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  - **Curated by:** Roman
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+ - **Funded by Roman:** No funding needed
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  - **Shared by Roman:** Also made by Roman
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  - **Language(s) (NLP):** English
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  - **License:** Common Creatives Attribution Share Alike 4.0
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  ### Dataset Sources [optional]
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+ - **Repository:** [https://huggingface.co/datasets/DataMuncher-Labs/LaTeXt]
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  - **I don't write papers or demos**
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  ## Uses
 
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  <!-- This section describes suitable use cases for the dataset. -->
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+ Post training for mathematical visualization.
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  ### Out-of-Scope Use
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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+ The dataset uses the format of
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  problem_latex|solution_latex|problem_english
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  <!-- Motivation for the creation of this dataset. -->
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+ I thought there was simply a lack of mathematical Latex datasets
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  ### Source Data
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  <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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+ Data was sourced from python...
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  **Its synthetic data**
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  <!--*I don't upload webscraped data cause im afraid i could get copyrighted ;-;*-->
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  <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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+ Roman
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+ <!--Ai assisted in making some parts of the script (sympy is hard)-->
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  #### Personal and Sensitive Information
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  <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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+ No PII or Sensitive information
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  *Also why I make synthtic data*
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+ #### Doesn't cover all equation types
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+ #### Doesn't cover all numbers possible
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+ #### There are aready similar datasets
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  ### Recommendations
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  **BibTeX:**
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+ @dataset{datamuncher_latext_2026,
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  author = {DataMuncher-Labs},
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+ title = {LaTeXt},
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  year = {2026},
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  publisher = {Hugging Face},
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+ url = {https://huggingface.co/datasets/DataMuncher-Labs/LaTeXt},
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+ note = {Synthetic LaTeX equation text dataset}
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  }
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  **APA:**
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+ **DataMuncher-Labs. (2026). LaTeXt [Dataset]. Hugging Face. https://huggingface.co/datasets/DataMuncher-Labs/LaTeXt**
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  ## Dataset Card Authors