mlsanityData to 7 Oct 2026

Graph Neural Networks and Representation Embedding for Table Extraction in PDF Documents

arXiv 2208.11203 ↗First posted 23 Aug 2022cs.CVcited by 6

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Abstract (arXiv)

Tables are widely used in several types of documents since they can bring important information in a structured way. In scientific papers, tables can sum up novel discoveries and summarize experimental results, making the research comparable and easily understandable by scholars. Several methods perform table analysis working on document images, losing useful information during the conversion from the PDF files since OCR tools can be prone to recognition errors, in particular for text inside tables. The main contribution of this work is to tackle the problem of table extraction, exploiting Graph Neural Networks. Node features are enriched with suitably designed representation embeddings. These representations help to better distinguish not only tables from the other parts of the paper, but also table cells from table headers. We experimentally evaluated the proposed approach on a new dataset obtained by merging the information provided in the PubLayNet and PubTables-1M datasets.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 21 of its 49 references that are in the map. First posted on arXiv 23 Aug 2022.

Builds on

21 of 49 references.

References · 21

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9 more
  1. 2020AxCell: Automatic Extraction of Results from Machine Learning Paperscited by 48
  2. 2021LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignmentcited by 46
  3. 2021VSR: A Unified Framework for Document Layout Analysis combining Vision, Semantics and Relationscited by 40
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  5. 2021TGRNet: A Table Graph Reconstruction Network for Table Structure Recognitioncited by 27
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 0; 2025: 2; 2026: 2.

6 papers.

  1. 2023A Graphical Approach to Document Layout Analysiscited by 8
  2. 2025Benchmarking Graph Neural Networks for Document Layout Analysis in Public Affairscited by 6
  3. 2023CTE: A Dataset for Contextualized Table Extractioncited by 3
  4. 2025An agentic system with reinforcement-learned subsystem improvements for parsing form-like documentscited by 1
  5. 2026Visual-Aware Representation of Web Pages for Machine Learning Applicationscited by 0
  6. 2026Enhancing Table Structure Recognition via Bounding Box Guidancecited by 0