mlsanityData to 14 Oct 2026

TabLeX: A Benchmark Dataset for Structure and Content Information Extraction from Scientific Tables

arXiv 2105.06400 ↗First posted 12 May 2021cs.IR cs.LGcited by 15

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Abstract (arXiv)

Information Extraction (IE) from the tables present in scientific articles is challenging due to complicated tabular representations and complex embedded text. This paper presents TabLeX, a large-scale benchmark dataset comprising table images generated from scientific articles. TabLeX consists of two subsets, one for table structure extraction and the other for table content extraction. Each table image is accompanied by its corresponding LATEX source code. To facilitate the development of robust table IE tools, TabLeX contains images in different aspect ratios and in a variety of fonts. Our analysis sheds light on the shortcomings of current state-of-the-art table extraction models and shows that they fail on even simple table images. Towards the end, we experiment with a transformer-based existing baseline to report performance scores. In contrast to the static benchmarks, we plan to augment this dataset with more complex and diverse tables at regular intervals.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). Builds on 14 of its 33 references that are in the map. First posted on arXiv 12 May 2021.

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14 of 33 references.

References · 14

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2 more
  1. 2020Scene Text Recognition via Transformercited by 7
  2. 2019Rethinking Table Recognition using Graph Neural Networkscited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 7; 2025: 3; 2026: 2.

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  1. 2024OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotationscited by 150
  2. 2021Document AI: Benchmarks, Models and Applicationscited by 62
  3. 2024Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extractioncited by 44
  4. 2023A large-scale dataset for end-to-end table recognition in the wildcited by 24
  5. 2023LORE: Logical Location Regression Network for Table Structure Recognitioncited by 19
  6. 2024FREB-TQA: A Fine-Grained Robustness Evaluation Benchmark for Table Question Answeringcited by 16
  7. 2024READoc: A Unified Benchmark for Realistic Document Structured Extractioncited by 15
  8. 2025Benchmarking Multimodal LLMs on Recognition and Understanding over Chemical Tablescited by 13
  9. 2024LORE++: Logical Location Regression Network for Table Structure Recognition with Pre-trainingcited by 8
  10. 2024Uni-SMART: Universal Science Multimodal Analysis and Research Transformercited by 7
  11. 2025SPRINT: Script-agnostic Structure Recognition in Tablescited by 6
  12. 2024Synthesizing Realistic Data for Table Recognitioncited by 2
3 more
  1. 2026Building Agent Harnesses for Scientific Curation from Multimodal Sourcescited by 1
  2. 2025ModelTables: A Corpus of Tables about Modelscited by 0
  3. 2026Code as Representation: A Compilable Parsing Paradigm for Academic Documentscited by 0