mlsanityData to 7 Oct 2026

ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short Summaries

arXiv 2304.13620 ↗First posted 26 Apr 2023cs.CL cs.LGcited by 30

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Abstract (arXiv)

Automatic chart to text summarization is an effective tool for the visually impaired people along with providing precise insights of tabular data in natural language to the user. A large and well-structured dataset is always a key part for data driven models. In this paper, we propose ChartSumm: a large-scale benchmark dataset consisting of a total of 84,363 charts along with their metadata and descriptions covering a wide range of topics and chart types to generate short and long summaries. Extensive experiments with strong baseline models show that even though these models generate fluent and informative summaries by achieving decent scores in various automatic evaluation metrics, they often face issues like suffering from hallucination, missing out important data points, in addition to incorrect explanation of complex trends in the charts. We also investigated the potential of expanding ChartSumm to other languages using automated translation tools. These make our dataset a challenging benchmark for future research.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Builds on 25 of its 41 references that are in the map. First posted on arXiv 26 Apr 2023.

Builds on

25 of 41 references.

References · 25

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  4. 2014CIDEr: Consensus-based Image Description Evaluationcited by 2,027
  5. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,813
  6. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,790
  7. 2022ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoningcited by 1,449
  8. 2022No Language Left Behind: Scaling Human-Centered Machine Translationcited by 1,290
  9. 2020BLEURT: Learning Robust Metrics for Text Generationcited by 1,196
  10. 2021XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languagescited by 346
  11. 2017Challenges in Data-to-Document Generationcited by 226
  12. 2022Chart-to-Text: A Large-Scale Benchmark for Chart Summarizationcited by 166
13 more
  1. 2020Chart-to-Text: Generating Natural Language Descriptions for Charts by Adapting the Transformer Modelcited by 77
  2. 2021SciCap: Generating Captions for Scientific Figurescited by 76
  3. 2022OpenCQA: Open-ended Question Answering with Chartscited by 60
  4. 2022Chart Question Answering: State of the Art and Future Directionscited by 26
  5. 2020WSL-DS: Weakly Supervised Learning with Distant Supervision for Query Focused Multi-Document Abstractive Summarizationcited by 23
  6. 2021Domain Adaptation with Pre-trained Transformers for Query Focused Abstractive Text Summarizationcited by 21
  7. 2022BLINK with Elasticsearch for Efficient Entity Linking in Business Conversationscited by 13
  8. 2021AutoChart: A Dataset for Chart-to-Text Generation Taskcited by 12
  9. 2020Reverse-engineering Bar Charts Using Neural Networkscited by 8
  10. 2020Efficient Inference For Neural Machine Translationcited by 7
  11. 2022Improving Named Entity Recognition in Telephone Conversations via Effective Active Learning with Human in the Loopcited by 7
  12. 2021Data-to-text Generation by Splicing Together Nearest Neighborscited by 4
  13. 2020Tensor Fields for Data Extraction from Chart Images: Bar Charts and Scatter Plotscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 9; 2025: 12; 2026: 7.

30 papers.

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  1. 2023A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasetscited by 123
  2. 2024ChartMimic: Evaluating LMM's Cross-Modal Reasoning Capability via Chart-to-Code Generationcited by 118
  3. 2023ChartBench: A Benchmark for Complex Visual Reasoning in Chartscited by 116
  4. 2024A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendationscited by 84
  5. 2024From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Modelscited by 52
  6. 2024VisEval: A Benchmark for Data Visualization in the Era of Large Language Modelscited by 43
  7. 2025Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluationcited by 41
  8. 2024Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction Tuningcited by 27
  9. 2024DataNarrative: Automated Data-Driven Storytelling with Visualizations and Textscited by 25
  10. 2024Synthesize Step-by-Step: Tools, Templates and LLMs as Data Generators for Reasoning-Based Chart VQAcited by 18
  11. 2025Unmasking Deceptive Visuals: Benchmarking Multimodal Large Language Models on Misleading Chart Question Answeringcited by 14
  12. 2025ChartCap: Mitigating Hallucination of Dense Chart Captioningcited by 7
18 more
  1. 2024Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directionscited by 5
  2. 2025Chart-HQA: A Benchmark for Hypothetical Question Answering in Chartscited by 5
  3. 2024ChartAdapter: Large Vision-Language Model for Chart Summarizationcited by 4
  4. 2025Do Large Multimodal Models Solve Caption Generation for Scientific Figures? Lessons Learned from SciCap Challenge 2023cited by 4
  5. 2025POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answeringcited by 3
  6. 2025From Charts to Fair Narratives: Uncovering and Mitigating Geo-Economic Biases in Chart-to-Textcited by 2
  7. 2026ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Modelscited by 2
  8. 2026Making Multimodal LLMs Reliable Chart Data Extractors: A Benchmark and Training Frameworkcited by 2
  9. 2025Data Metabolism: An Efficient Data Design Schema For Vision Language Modelcited by 1
  10. 2025Multi-Agent Multimodal Large Language Model Framework for Automated Interpretation of Fuel Efficiency Analytics in Public Transportationcited by 1
  11. 2025ChartAnchor: Chart Grounding with Structural-Semantic Fidelitycited by 1
  12. 2026Multimodal Information Fusion for Chart Understanding: A Survey of MLLMs -- Evolution, Limitations, and Cognitive Enhancementcited by 1
  13. 2026Beyond Description: A Multimodal Agent Framework for Insightful Chart Summarizationcited by 1
  14. 2026DATAREEL: Automated Data-Driven Video Story Generation with Animationscited by 1
  15. 2025Capybara-OMNI: An Efficient Paradigm for Building Omni-Modal Language Modelscited by 0
  16. 2025Benchmark It Yourself (BIY): Preparing a Dataset and Benchmarking AI Models for Scatterplot-Related Taskscited by 0
  17. 2026REChart: Reasoning-Efficient Chart Editing with Large Reasoning Modelscited by 0
  18. 2026SciFigure2Code: An AI-Reconstructed Benchmark for Scientific Figure-to-Codecited by 0