mlsanityData to 7 Oct 2026

SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images

arXiv 2301.04883 ↗First posted 12 Jan 2023cs.CL cs.CVcited by 175

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Cited by 56 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Visual question answering on document images that contain textual, visual, and layout information, called document VQA, has received much attention recently. Although many datasets have been proposed for developing document VQA systems, most of the existing datasets focus on understanding the content relationships within a single image and not across multiple images. In this study, we propose a new multi-image document VQA dataset, SlideVQA, containing 2.6k+ slide decks composed of 52k+ slide images and 14.5k questions about a slide deck. SlideVQA requires complex reasoning, including single-hop, multi-hop, and numerical reasoning, and also provides annotated arithmetic expressions of numerical answers for enhancing the ability of numerical reasoning. Moreover, we developed a new end-to-end document VQA model that treats evidence selection and question answering in a unified sequence-to-sequence format. Experiments on SlideVQA show that our model outperformed existing state-of-the-art QA models, but that it still has a large gap behind human performance. We believe that our dataset will facilitate research on document VQA.

Key facts. Cited by 175 papers in the map (data through 7 Oct 2026). Builds on 38 of its 46 references that are in the map. First posted on arXiv 12 Jan 2023.

Builds on

38 of 46 references.

References · 38

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  4. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
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  9. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  10. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,686
  11. 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,538
  12. 2020DocVQA: A Dataset for VQA on Document Imagescited by 1,288
26 more
  1. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  2. 2016An overview of gradient descent optimization algorithmscited by 1,021
  3. 2019DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphscited by 883
  4. 2019LayoutLM: Pre-training of Text and Layout for Document Image Understandingcited by 549
  5. 2018TVQA: Localized, Compositional Video Question Answeringcited by 463
  6. 2021InfographicVQAcited by 430
  7. 2018The Web as a Knowledge-base for Answering Complex Questionscited by 409
  8. 2020LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understandingcited by 406
  9. 2015MovieQA: Understanding Stories in Movies through Question-Answeringcited by 304
  10. 2021MultiModalQA: Complex Question Answering over Text, Tables and Imagescited by 177
  11. 2019TVQA+: Spatio-Temporal Grounding for Video Question Answeringcited by 153
  12. 2021VisualMRC: Machine Reading Comprehension on Document Imagescited by 150
  13. 2021Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformercited by 134
  14. 2020Injecting Numerical Reasoning Skills into Language Modelscited by 133
  15. 2021End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answeringcited by 133
  16. 2021WebSRC: A Dataset for Web-Based Structural Reading Comprehensioncited by 98
  17. 2021End-to-End Training of Neural Retrievers for Open-Domain Question Answeringcited by 75
  18. 2021DOC2PPT: Automatic Presentation Slides Generation from Scientific Documentscited by 68
  19. 2020Do Language Embeddings Capture Scales?cited by 63
  20. 2019Select, Answer and Explain: Interpretable Multi-hop Reading Comprehension over Multiple Documentscited by 57
  21. 2021D2S: Document-to-Slide Generation Via Query-Based Text Summarizationcited by 48
  22. 2021Document Collection Visual Question Answeringcited by 45
  23. 2021Turning Tables: Generating Examples from Semi-structured Tables for Endowing Language Models with Reasoning Skillscited by 39
  24. 2020Visual Question Answering on Image Setscited by 26
  25. 2020Video-Grounded Dialogues with Pretrained Generation Language Modelscited by 16
  26. 2021NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Datasetcited by 14

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 32; 2025: 71; 2026: 67.

175 papers.

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  2. 2024VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documentscited by 237
  3. 2024MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizationscited by 174
  4. 2024OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoningcited by 165
  5. 2023Document Understanding Dataset and Evaluation (DUDE)cited by 132
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  7. 2025Baichuan-Omni-1.5 Technical Reportcited by 107
  8. 2024MileBench: Benchmarking MLLMs in Long Contextcited by 86
  9. 2023X-InstructBLIP: A Framework for aligning X-Modal instruction-aware representations to LLMs and Emergent Cross-modal Reasoningcited by 78
  10. 2023Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructionscited by 76
  11. 2024SPIQA: A Dataset for Multimodal Question Answering on Scientific Paperscited by 75
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38 more
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  7. 2024From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Modelscited by 52
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  9. 2025MMDocIR: Benchmarking Multimodal Retrieval for Long Documentscited by 43
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  11. 2024MC-Bench: A Benchmark for Multi-Context Visual Grounding in the Era of MLLMscited by 38
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  13. 2024Assessment of Multimodal Large Language Models in Alignment with Human Valuescited by 36
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  15. 2025REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmarkcited by 34
  16. 2025Benchmarking Retrieval-Augmented Multimodal Generation for Document Question Answeringcited by 33
  17. 2024InstructDoc: A Dataset for Zero-Shot Generalization of Visual Document Understanding with Instructionscited by 27
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  19. 2025SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinementcited by 27
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  22. 2024SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understandingcited by 25
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  27. 2024Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ Documentscited by 17
  28. 2025MoLoRAG: Bootstrapping Document Understanding via Multi-modal Logic-aware Retrievalcited by 17
  29. 2025Visual-RAG: Benchmarking Text-to-Image Retrieval Augmented Generation for Visual Knowledge Intensive Queriescited by 16
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  31. 2024PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse Samplingcited by 14
  32. 2025VisR-Bench: An Empirical Study on Visual Retrieval-Augmented Generation for Multilingual Long Document Understandingcited by 13
  33. 2024StrucTexTv3: An Efficient Vision-Language Model for Text-rich Image Perception, Comprehension, and Beyondcited by 11
  34. 2025PosterSum: A Multimodal Benchmark for Scientific Poster Summarizationcited by 10
  35. 2024JDocQA: Japanese Document Question Answering Dataset for Generative Language Modelscited by 9
  36. 2025Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understandingcited by 9
  37. 2024RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering and Clinical Reasoningcited by 8
  38. 2024One missing piece in Vision and Language: A Survey on Comics Understandingcited by 8

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