eSciBench: An Extensible Scientific PDF Extraction Benchmark

Noah Tremblay Taillon; Philippe Langlais

doi:10.63317/4sxku4i2piqq

eSciBench: An Extensible Scientific PDF Extraction Benchmark

Noah Tremblay Taillon, Phillippe Langlais

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Abstract

Automatically extracting information from PDF documents (such as authors, affiliations, references, tables, equations) may be transformative in Digital Humanities where meta-data accompanying a document is typically manually collected, a cumbersome process. In this work, we conduct a systematic benchmarking of PDF extractors on a set of 100 scientific articles (1949 pages) of the STEM domain that have been processed automatically, then carefully curated. Our benchmark, named eSciBench is openly accessible. Putting to the test 13 extractors on it reveals that although some extractors perform well overall, extracting information from scientific articles is far from a solved problem.

Anthology ID:: 2026.lrec-1.600
Volume:: Proceedings of the Fifteenth Language Resources and Evaluation Conference
Month:: May
Year:: 2026
Address:: Palma de Mallorca, Spain
Editors:: Stelios Piperidis, Núria Bel, Henk van den Heuvel, Nancy Ide, Simon Krek, Antonio Toral
Venue:: LREC
SIG:
Publisher:: ELRA Language Resource Association
Note:
Pages:: 7568–7580
Language:
External URL:: https://lrec.elra.info/lrec2026-main-600
DOI:: 10.63317/4sxku4i2piqq
Bibkey:
Cite (ACL):: Noah Tremblay Taillon and Phillippe Langlais. 2026. eSciBench: An Extensible Scientific PDF Extraction Benchmark. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 7568–7580, Palma de Mallorca, Spain. ELRA Language Resource Association.
Cite (Informal):: eSciBench: An Extensible Scientific PDF Extraction Benchmark (Tremblay Taillon & Langlais, LREC 2026)
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@inproceedings{tremblay-taillon-langlais-2026-escibench,
    title = "e{S}ci{B}ench: An Extensible Scientific {PDF} Extraction Benchmark",
    author = "Tremblay Taillon, Noah  and
      Langlais, Phillippe",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://aclanthology.org/2026.lrec-1.600/",
    doi = "10.63317/4sxku4i2piqq",
    pages = "7568--7580",
    abstract = "Automatically extracting information from PDF documents (such as authors, affiliations, references, tables, equations) may be transformative in Digital Humanities where meta-data accompanying a document is typically manually collected, a cumbersome process. In this work, we conduct a systematic benchmarking of PDF extractors on a set of 100 scientific articles (1949 pages) of the STEM domain that have been processed automatically, then carefully curated. Our benchmark, named eSciBench is openly accessible. Putting to the test 13 extractors on it reveals that although some extractors perform well overall, extracting information from scientific articles is far from a solved problem."
}

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%0 Conference Proceedings
%T eSciBench: An Extensible Scientific PDF Extraction Benchmark
%A Tremblay Taillon, Noah
%A Langlais, Phillippe
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F tremblay-taillon-langlais-2026-escibench
%X Automatically extracting information from PDF documents (such as authors, affiliations, references, tables, equations) may be transformative in Digital Humanities where meta-data accompanying a document is typically manually collected, a cumbersome process. In this work, we conduct a systematic benchmarking of PDF extractors on a set of 100 scientific articles (1949 pages) of the STEM domain that have been processed automatically, then carefully curated. Our benchmark, named eSciBench is openly accessible. Putting to the test 13 extractors on it reveals that although some extractors perform well overall, extracting information from scientific articles is far from a solved problem.
%R 10.63317/4sxku4i2piqq
%U https://aclanthology.org/2026.lrec-1.600/
%U https://doi.org/10.63317/4sxku4i2piqq
%P 7568-7580

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Markdown (Informal)

[eSciBench: An Extensible Scientific PDF Extraction Benchmark](https://aclanthology.org/2026.lrec-1.600/) (Tremblay Taillon & Langlais, LREC 2026)

eSciBench: An Extensible Scientific PDF Extraction Benchmark (Tremblay Taillon & Langlais, LREC 2026)

ACL

Noah Tremblay Taillon and Phillippe Langlais. 2026. eSciBench: An Extensible Scientific PDF Extraction Benchmark. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 7568–7580, Palma de Mallorca, Spain. ELRA Language Resource Association.