mlsanityData to 14 Oct 2026

Chart Question Answering from Real-World Analytical Narratives

arXiv 2507.01627 ↗First posted 2 Jul 2025cs.CLcited by 3

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Abstract (arXiv)

We present a new dataset for chart question answering (CQA) constructed from visualization notebooks. The dataset features real-world, multi-view charts paired with natural language questions grounded in analytical narratives. Unlike prior benchmarks, our data reflects ecologically valid reasoning workflows. Benchmarking state-of-the-art multimodal large language models reveals a significant performance gap, with GPT-4.1 achieving an accuracy of 69.3%, underscoring the challenges posed by this more authentic CQA setting.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 7 of its 14 references that are in the map. First posted on arXiv 2 Jul 2025.

Builds on

7 of 14 references.

References · 7

  1. 2022ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoningcited by 1,479
  2. 2018DVQA: Understanding Data Visualizations via Question Answeringcited by 340
  3. 2017FigureQA: An Annotated Figure Dataset for Visual Reasoningcited by 319
  4. 2024CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMscited by 234
  5. 2022All You May Need for VQA are Image Captionscited by 65
  6. 2019LEAF-QA: Locate, Encode & Attend for Figure Question Answeringcited by 54
  7. 2024MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart Problemscited by 24

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026ChartArena: Benchmarking Chart Parsing across Languages, Scenarios, and Formatscited by 2
  2. 2026Beyond Single Plots: A Benchmark for Question Answering on Multi-Chartscited by 0
  3. 2026Attention-Guided Saliency Maps for Interpreting Visualization Literacy in VLMscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering
  2. 2025ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering
  3. 2024ChartInsights: Evaluating Multimodal Large Language Models for Low-Level Chart Question Answering
  4. 2024Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction Tuning
  5. 2023DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense Understanding
  6. 2024Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustness
  7. 2025Chart-HQA: A Benchmark for Hypothetical Question Answering in Charts
  8. 2025POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering