mlsanityData to 7 Oct 2026

DVQA: Understanding Data Visualizations via Question Answering

arXiv 1801.08163 ↗First posted 24 Jan 2018cs.CV cs.GRcited by 338

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Cited by 185 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Bar charts are an effective way to convey numeric information, but today's algorithms cannot parse them. Existing methods fail when faced with even minor variations in appearance. Here, we present DVQA, a dataset that tests many aspects of bar chart understanding in a question answering framework. Unlike visual question answering (VQA), DVQA requires processing words and answers that are unique to a particular bar chart. State-of-the-art VQA algorithms perform poorly on DVQA, and we propose two strong baselines that perform considerably better. Our work will enable algorithms to automatically extract numeric and semantic information from vast quantities of bar charts found in scientific publications, Internet articles, business reports, and many other areas.

Key facts. Cited by 338 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Jan 2018.

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Citing papers per year: 2021: 15; 2022: 13; 2023: 32; 2024: 109; 2025: 101; 2026: 68.

338 papers.

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  11. 2021InfographicVQAcited by 430
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38 more
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  7. 2021IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoningcited by 262
  8. 2025LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RLcited by 244
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  13. 2024MANTIS: Interleaved Multi-Image Instruction Tuningcited by 212
  14. 2024NVILA: Efficient Frontier Visual Language Modelscited by 206
  15. 2024InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Outputcited by 195
  16. 2025MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipecited by 174
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  18. 2024Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Searchcited by 171
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  20. 2024OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoningcited by 165
  21. 2023UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoningcited by 158
  22. 2024InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HDcited by 156
  23. 2021VisualMRC: Machine Reading Comprehension on Document Imagescited by 150
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  25. 2023UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Modelcited by 143
  26. 2024Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Modelscited by 138
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  28. 2024Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoderscited by 137
  29. 2024Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoningcited by 136
  30. 2024VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Taskscited by 136
  31. 2021Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformercited by 134
  32. 2025VisualPRM: An Effective Process Reward Model for Multimodal Reasoningcited by 134
  33. 2024Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Modelscited by 133
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  37. 2024MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scalecited by 125
  38. 2022A Survey of Deep Learning for Mathematical Reasoningcited by 124

50 most cited of 338 All 338 (JSON)