mlsanityData to 14 Oct 2026

V-Doc : Visual questions answers with Documents

arXiv 2205.13724 ↗First posted 27 May 2022cs.AI cs.CVcited by 19

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Abstract (arXiv)

We propose V-Doc, a question-answering tool using document images and PDF, mainly for researchers and general non-deep learning experts looking to generate, process, and understand the document visual question answering tasks. The V-Doc supports generating and using both extractive and abstractive question-answer pairs using documents images. The extractive QA selects a subset of tokens or phrases from the document contents to predict the answers, while the abstractive QA recognises the language in the content and generates the answer based on the trained model. Both aspects are crucial to understanding the documents, especially in an image format. We include a detailed scenario of question generation for the abstractive QA task. V-Doc supports a wide range of datasets and models, and is highly extensible through a declarative, framework-agnostic platform.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Builds on 15 of its 19 references that are in the map. First posted on arXiv 27 May 2022.

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15 of 19 references.

References · 15

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2016CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoningcited by 1,457
  4. 2020DocVQA: A Dataset for VQA on Document Imagescited by 1,317
  5. 2019VisualBERT: A Simple and Performant Baseline for Vision and Languagecited by 1,296
  6. 2020LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understandingcited by 408
  7. 2019PubLayNet: largest dataset ever for document layout analysiscited by 351
  8. 2019FUNSD: A Dataset for Form Understanding in Noisy Scanned Documentscited by 349
  9. 2019PlotQA: Reasoning over Scientific Plotscited by 321
  10. 2017FigureQA: An Annotated Figure Dataset for Visual Reasoningcited by 319
  11. 2016Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Groundingcited by 243
  12. 2015Evaluation of Deep Convolutional Nets for Document Image Classification and Retrievalcited by 213
3 more
  1. 2018Compositional Attention Networks for Machine Reasoningcited by 183
  2. 2021VisualMRC: Machine Reading Comprehension on Document Imagescited by 151
  3. 2018Dynamic Fusion with Intra- and Inter- Modality Attention Flow for Visual Question Answeringcited by 114

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 2; 2024: 6; 2025: 6; 2026: 3.

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  1. 2025MDocAgent: A Multi-Modal Multi-Agent Framework for Document Understandingcited by 67
  2. 2024VisDoM: Multi-Document QA with Visually Rich Elements Using Multimodal Retrieval-Augmented Generationcited by 41
  3. 2024HRVDA: High-Resolution Visual Document Assistantcited by 37
  4. 2023PDFVQA: A New Dataset for Real-World VQA on PDF Documentscited by 28
  5. 2025SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinementcited by 28
  6. 2024Deep Learning based Visually Rich Document Content Understanding: A Surveycited by 21
  7. 2022Doc-GCN: Heterogeneous Graph Convolutional Networks for Document Layout Analysiscited by 17
  8. 2025MoLoRAG: Bootstrapping Document Understanding via Multi-modal Logic-aware Retrievalcited by 17
  9. 2026DocDancer: Towards Agentic Document-Grounded Information Seekingcited by 12
  10. 2025Structured Attention Matters to Multimodal LLMs in Document Understandingcited by 8
  11. 2024PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answeringcited by 7
  12. 20243MVRD: Multimodal Multi-task Multi-teacher Visually-Rich Form Document Understandingcited by 3
7 more
  1. 2022PiggyBack: Pretrained Visual Question Answering Environment for Backing up Non-deep Learning Professionalscited by 2
  2. 2025ALDEN: Reinforcement Learning for Active Navigation and Evidence Gathering in Long Documentscited by 2
  3. 2024DistilDoc: Knowledge Distillation for Visually-Rich Document Applicationscited by 1
  4. 2023Workshop on Document Intelligence Understandingcited by 0
  5. 2025Joint Extraction Matters: Prompt-Based Visual Question Answering for Multi-Field Document Information Extractioncited by 0
  6. 2026What Does Your Short-Answer VQA Score Actually Measure? Evaluator-Dependent Instability in Multimodal Short-Answer Benchmarkscited by 0
  7. 2026D2-ScaleAgent: Dual-Dimensional Scaling for Long Document Understandingcited by 0