mlsanityData to 7 Oct 2026

Business Document Information Extraction: Towards Practical Benchmarks

arXiv 2206.11229 ↗First posted 20 Jun 2022cs.IR cs.AI cs.CVcited by 11

Not on the map. Why?

Abstract (arXiv)

Information extraction from semi-structured documents is crucial for frictionless business-to-business (B2B) communication. While machine learning problems related to Document Information Extraction (IE) have been studied for decades, many common problem definitions and benchmarks do not reflect domain-specific aspects and practical needs for automating B2B document communication. We review the landscape of Document IE problems, datasets and benchmarks. We highlight the practical aspects missing in the common definitions and define the Key Information Localization and Extraction (KILE) and Line Item Recognition (LIR) problems. There is a lack of relevant datasets and benchmarks for Document IE on semi-structured business documents as their content is typically legally protected or sensitive. We discuss potential sources of available documents including synthetic data.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 47 of its 96 references that are in the map. First posted on arXiv 20 Jun 2022.

Builds on

47 of 96 references.

References · 47

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  2. 2020DocVQA: A Dataset for VQA on Document Imagescited by 1,288
  3. 2019LayoutLM: Pre-training of Text and Layout for Document Image Understandingcited by 549
  4. 2016Neural Architectures for Named Entity Recognitioncited by 548
  5. 2021InfographicVQAcited by 430
  6. 2019TabFact: A Large-scale Dataset for Table-based Fact Verificationcited by 425
  7. 2021TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Financecited by 402
  8. 2019PubLayNet: largest dataset ever for document layout analysiscited by 349
  9. 2019FUNSD: A Dataset for Form Understanding in Noisy Scanned Documentscited by 345
  10. 2019PlotQA: Reasoning over Scientific Plotscited by 317
  11. 2019Character Region Awareness for Text Detectioncited by 273
  12. 2020HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Datacited by 263
35 more
  1. 2021ICDAR2019 Competition on Scanned Receipt OCR and Information Extractioncited by 254
  2. 2018The Natural Language Decathlon: Multitask Learning as Question Answeringcited by 235
  3. 2019Image-based table recognition: data, model, and evaluationcited by 233
  4. 2015Evaluation of Deep Convolutional Nets for Document Image Classification and Retrievalcited by 212
  5. 2020Open Question Answering over Tables and Textcited by 163
  6. 2020Global Table Extractor (GTE): A Framework for Joint Table Identification and Cell Structure Recognition Using Visual Contextcited by 146
  7. 2019ICDAR2019 Robust Reading Challenge on Multi-lingual Scene Text Detection and Recognition -- RRC-MLT-2019cited by 138
  8. 2020Towards Accurate Scene Text Recognition with Semantic Reasoning Networkscited by 131
  9. 2015Ask Me Anything: Dynamic Memory Networks for Natural Language Processingcited by 116
  10. 2021LayoutXLM: Multimodal Pre-training for Multilingual Visually-rich Document Understandingcited by 103
  11. 2019TableBank: A Benchmark Dataset for Table Detection and Recognitioncited by 102
  12. 2018Chargrid: Towards Understanding 2D Documentscited by 100
  13. 2020CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documentscited by 98
  14. 2021WebSRC: A Dataset for Web-Based Structural Reading Comprehensioncited by 98
  15. 2022TableFormer: Table Structure Understanding with Transformerscited by 93
  16. 2021Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layoutscited by 82
  17. 2020PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networkscited by 70
  18. 2021Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solutioncited by 64
  19. 2019BERTgrid: Contextualized Embedding for 2D Document Representation and Understandingcited by 63
  20. 2020Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)cited by 56
  21. 2019LEAF-QA: Locate, Encode & Attend for Figure Question Answeringcited by 53
  22. 2020LAMBERT: Layout-Aware (Language) Modeling for information extractioncited by 53
  23. 2020AxCell: Automatic Extraction of Results from Machine Learning Paperscited by 48
  24. 2021Spatial Dual-Modality Graph Reasoning for Key Information Extractioncited by 43
  25. 2018Extracting Scientific Figures with Distantly Supervised Neural Networkscited by 36
  26. 2017CloudScan - A configuration-free invoice analysis system using recurrent neural networkscited by 33
  27. 2018Attend, Copy, Parse -- End-to-end information extraction from documentscited by 25
  28. 2017A Survey on Optical Character Recognition Systemcited by 23
  29. 2019CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractorcited by 21
  30. 2019Table understanding in structured documentscited by 11
  31. 2018Adversarial TableQA: Attention Supervision for Question Answering on Tablescited by 10
  32. 2019One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesiscited by 8
  33. 2021Key Information Extraction From Documents: Evaluation And Generatorcited by 7
  34. 2019One-Shot Template Matching for Automatic Document Data Capturecited by 5
  35. 2020Learning from similarity and information extraction from structured documentscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 3; 2025: 0; 2026: 5.

11 papers.

  1. 2023DocILE Benchmark for Document Information Localization and Extractioncited by 58
  2. 2023Beyond Document Page Classification: Design, Datasets, and Challengescited by 10
  3. 2024GLiNER multi-task: Generalist Lightweight Model for Various Information Extraction Taskscited by 8
  4. 2024Deep Learning based Key Information Extraction from Business Documents: Systematic Literature Reviewcited by 6
  5. 2026UNIKIE-BENCH: Benchmarking Large Multimodal Models for Key Information Extraction in Visual Documentscited by 4
  6. 2026The Million-Label NER: Breaking Scale Barriers with GLiNER bi-encodercited by 4
  7. 2024Retrieval Augmented Structured Generation: Business Document Information Extraction As Tool Usecited by 3
  8. 2023DocILE 2023 Teaser: Document Information Localization and Extractioncited by 1
  9. 2026Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesiscited by 1
  10. 2026Multimodal Approaches for Visually-Rich Document Type Classification: A Comparative Analysiscited by 0
  11. 2026DocAnnot -- Accelerating the Creation of Key Information Extraction Datasets with GenAI-Powered Auto-annotationcited by 0