mlsanityData to 7 Oct 2026

BoundingDocs: a Unified Dataset for Document Question Answering with Spatial Annotations

arXiv 2501.03403 ↗First posted 6 Jan 2025cs.CL cs.AIcited by 8

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Abstract (arXiv)

We present a unified dataset for document Question-Answering (QA), which is obtained combining several public datasets related to Document AI and visually rich document understanding (VRDU). Our main contribution is twofold: on the one hand we reformulate existing Document AI tasks, such as Information Extraction (IE), into a Question-Answering task, making it a suitable resource for training and evaluating Large Language Models; on the other hand, we release the OCR of all the documents and include the exact position of the answer to be found in the document image as a bounding box. Using this dataset, we explore the impact of different prompting techniques (that might include bounding box information) on the performance of open-weight models, identifying the most effective approaches for document comprehension.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 31 of its 55 references that are in the map. First posted on arXiv 6 Jan 2025.

Builds on

31 of 55 references.

References · 31

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  11. 2021InfographicVQAcited by 430
  12. 2021OCR-free Document Understanding Transformercited by 400
19 more
  1. 2019FUNSD: A Dataset for Form Understanding in Noisy Scanned Documentscited by 345
  2. 2021ICDAR2019 Competition on Scanned Receipt OCR and Information Extractioncited by 254
  3. 2024mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understandingcited by 220
  4. 2023SlideVQA: A Dataset for Document Visual Question Answering on Multiple Imagescited by 175
  5. 2021VisualMRC: Machine Reading Comprehension on Document Imagescited by 150
  6. 2023Document Understanding Dataset and Evaluation (DUDE)cited by 132
  7. 2023DocLLM: A layout-aware generative language model for multimodal document understandingcited by 112
  8. 2022Hierarchical multimodal transformers for Multi-Page DocVQAcited by 102
  9. 2022TableFormer: Table Structure Understanding with Transformerscited by 93
  10. 2021Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layoutscited by 82
  11. 2022End-to-end Document Recognition and Understanding with Dessurtcited by 73
  12. 2021Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solutioncited by 64
  13. 2023LMDX: Language Model-based Document Information Extraction and Localizationcited by 37
  14. 2022VRDU: A Benchmark for Visually-rich Document Understandingcited by 35
  15. 2023Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answeringcited by 24
  16. 2024ANLS* -- A Universal Document Processing Metric for Generative Large Language Modelscited by 10
  17. 2024LAPDoc: Layout-Aware Prompting for Documentscited by 9
  18. 2023FATURA: A Multi-Layout Invoice Image Dataset for Document Analysis and Understandingcited by 4
  19. 2024"What is the value of {templates}?" Rethinking Document Information Extraction Datasets for LLMscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 5.

8 papers.

  1. 2025DocVXQA: Context-Aware Visual Explanations for Document Question Answeringcited by 5
  2. 2025SciEGQA: A Dataset for Scientific Evidence-Grounded Question Answering and Reasoningcited by 4
  3. 2025Towards Reliable and Interpretable Document Question Answering via VLMscited by 2
  4. 2026ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Imagescited by 1
  5. 2026An LMM for Precisely Grounding Elements in Documentscited by 0
  6. 2026Stop Thinking, Start Looking: Efficient Post-Training for Multimodal Document Question Answering via Reasoning-Free Alignmentcited by 0
  7. 2026Valid Per-Field Selective Risk Control for Document Extraction: Three Failure Modes, a Validity Ladder, and When Conditioning Payscited by 0
  8. 2026DocAttriBench: Benchmarking Answer Grounding in Document Visual Question Answeringcited by 0