mlsanityData to 14 Oct 2026

LEAF-QA: Locate, Encode & Attend for Figure Question Answering

arXiv 1907.12861 ↗First posted 30 Jul 2019cs.CVcited by 54

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Abstract (arXiv)

We introduce LEAF-QA, a comprehensive dataset of 250,000 densely annotated figures/charts, constructed from real-world open data sources, along with ~2 million question-answer (QA) pairs querying the structure and semantics of these charts. LEAF-QA highlights the problem of multimodal QA, which is notably different from conventional visual QA (VQA), and has recently gained interest in the community. Furthermore, LEAF-QA is significantly more complex than previous attempts at chart QA, viz. FigureQA and DVQA, which present only limited variations in chart data. LEAF-QA being constructed from real-world sources, requires a novel architecture to enable question answering. To this end, LEAF-Net, a deep architecture involving chart element localization, question and answer encoding in terms of chart elements, and an attention network is proposed. Different experiments are conducted to demonstrate the challenges of QA on LEAF-QA. The proposed architecture, LEAF-Net also considerably advances the current state-of-the-art on FigureQA and DVQA.

Key facts. Cited by 54 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Jul 2019.

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Citing papers per year: 2021: 6; 2022: 7; 2023: 10; 2024: 12; 2025: 10; 2026: 9.

54 papers.

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  1. 2022ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoningcited by 1,479
  2. 2021InfographicVQAcited by 437
  3. 2021TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene textcited by 171
  4. 2023MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuningcited by 150
  5. 2025ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answeringcited by 108
  6. 2022MapQA: A Dataset for Question Answering on Choropleth Mapscited by 85
  7. 2024SPIQA: A Dataset for Multimodal Question Answering on Scientific Paperscited by 75
  8. 2023SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphscited by 68
  9. 2022ScreenQA: Large-Scale Question-Answer Pairs over Mobile App Screenshotscited by 66
  10. 2022OpenCQA: Open-ended Question Answering with Chartscited by 61
  11. 2024From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Modelscited by 53
  12. 20213D Question Answeringcited by 41
38 more
  1. 2023Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checkingcited by 35
  2. 2023PDFVQA: A New Dataset for Real-World VQA on PDF Documentscited by 28
  3. 2022Chart Question Answering: State of the Art and Future Directionscited by 26
  4. 2023From Image to Language: A Critical Analysis of Visual Question Answering (VQA) Approaches, Challenges, and Opportunitiescited by 25
  5. 2021ICDAR 2021 Competition on Document VisualQuestion Answeringcited by 19
  6. 2024Synthesize Step-by-Step: Tools, Templates and LLMs as Data Generators for Reasoning-Based Chart VQAcited by 19
  7. 2024Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustnesscited by 17
  8. 2023Enhanced Chart Understanding in Vision and Language Task via Cross-modal Pre-training on Plot Table Pairscited by 15
  9. 2022FETA: Towards Specializing Foundation Models for Expert Task Applicationscited by 13
  10. 2025BigCharts-R1: Enhanced Chart Reasoning with Visual Reinforcement Finetuningcited by 13
  11. 2023DOMINO: A Dual-System for Multi-step Visual Language Reasoningcited by 12
  12. 2021A survey on VQA_Datasets and Approachescited by 11
  13. 2021Classification-Regression for Chart Comprehensioncited by 11
  14. 2022Business Document Information Extraction: Towards Practical Benchmarkscited by 11
  15. 2025ChartQA-X: Generating Explanations for Visual Chart Reasoningcited by 10
  16. 2024mChartQA: A universal benchmark for multimodal Chart Question Answer based on Vision-Language Alignment and Reasoningcited by 9
  17. 2023RealCQA: Scientific Chart Question Answering as a Test-bed for First-Order Logiccited by 8
  18. 2025WikiMixQA: A Multimodal Benchmark for Question Answering over Tables and Chartscited by 8
  19. 2023FigCaps-HF: A Figure-to-Caption Generative Framework and Benchmark with Human Feedbackcited by 7
  20. 2024Understanding Graphical Perception in Data Visualization through Zero-shot Prompting of Vision-Language Modelscited by 6
  21. 2024SBS Figures: Pre-training Figure QA from Stage-by-Stage Synthesized Imagescited by 5
  22. 2025PRISMM-Bench: A Benchmark of Peer-Review Grounded Multimodal Inconsistenciescited by 4
  23. 2025START: Spatial and Textual Learning for Chart Understandingcited by 4
  24. 2026Beyond Human Annotation: Recent Advances in Data Generation Methods for Document Intelligencecited by 4
  25. 2023DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense Understandingcited by 3
  26. 2024GRAB: A Challenging GRaph Analysis Benchmark for Large Multimodal Modelscited by 3
  27. 2025Chart Question Answering from Real-World Analytical Narrativescited by 3
  28. 2024GoT-CQA: Graph-of-Thought Guided Compositional Reasoning for Chart Question Answeringcited by 2
  29. 2024ChartKG: A Knowledge-Graph-Based Representation for Chart Imagescited by 2
  30. 2025ChartGaze: Enhancing Chart Understanding in LVLMs with Eye-Tracking Guided Attention Refinementcited by 2
  31. 2024SimpsonsVQA: Enhancing Inquiry-Based Learning with a Tailored Datasetcited by 1
  32. 2026Multimodal Information Fusion for Chart Understanding: A Survey of MLLMs -- Evolution, Limitations, and Cognitive Enhancementcited by 1
  33. 2026Navigating the Mirage: A Dual-Path Agentic Framework for Robust Misleading Chart Question Answeringcited by 1
  34. 2026ChartAct: A Benchmark for Dynamic Chart Understandingcited by 1
  35. 2024MAPWise: Evaluating Vision-Language Models for Advanced Map Queriescited by 0
  36. 2025Patent Figure Classification using Large Vision-language Modelscited by 0
  37. 2025Benchmark It Yourself (BIY): Preparing a Dataset and Benchmarking AI Models for Scatterplot-Related Taskscited by 0
  38. 2026When Visuals Aren't the Problem: Evaluating Vision-Language Models on Misleading Data Visualizationscited by 0

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