Datasets › im2latex-100k

im2latex-100k

Introduced by Yuntian Deng et al. in Image-to-Markup Generation with Coarse-to-Fine Attention16 Sep 2016 archive 2025-07-28

A prebuilt dataset for OpenAI's task for image-2-latex system. Includes total of ~100k formulas and images splitted into train, validation and test sets. Formulas were parsed from LaTeX sources provided here: http://www.cs.cornell.edu/projects/kddcup/datasets.html(originally from arXiv)

Each image is a PNG image of fixed size. Formula is in black and rest of the image is transparent.

For related tools (eg. tokenizer) check out this repository: https://github.com/Miffyli/im2latex-dataset For pre-made evaluation scripts and built im2latex system check this repository: https://github.com/harvardnlp/im2markup

Newlines used in formulas_im2latex.lst are UNIX-style newlines (\n). Reading file with other type of newlines results to slightly wrong amount of lines (104563 instead of 103558), and thus breaks the structure used by this dataset. Python 3.x reads files using newlines of the running system by default, and to avoid this file must be opened with newlines="\n" (eg. open("formulas_im2latex.lst", newline="\n")).

Source: https://zenodo.org/record/56198#.YJjuCGZKgox

Image source: https://arxiv.org/pdf/1609.04938v2.pdf

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Optical Character Recognition (OCR) im2latex-100k I2L-STRIPS BLEU 88.86% Teaching Machines to Code: Neural Markup Generation with... untrix/im2latex 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 12. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Teaching Machines to Code: Neural Markup Generation with Visual Attention 1 1 15 Feb 2018 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC0 1.0 Universal

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • im2latex-100k

1 variant name, as the archive lists them.

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