mlsanityData to 7 Oct 2026

AutoChart: A Dataset for Chart-to-Text Generation Task

arXiv 2108.06897 ↗First posted 16 Aug 2021cs.CL cs.AI cs.MMcited by 12

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Abstract (arXiv)

The analytical description of charts is an exciting and important research area with many applications in academia and industry. Yet, this challenging task has received limited attention from the computational linguistics research community. This paper proposes textsfAutoChart, a large dataset for the analytical description of charts, which aims to encourage more research into this important area. Specifically, we offer a novel framework that generates the charts and their analytical description automatically. We conducted extensive human and machine evaluations on the generated charts and descriptions and demonstrate that the generated texts are informative, coherent, and relevant to the corresponding charts.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 12 of its 25 references that are in the map. First posted on arXiv 16 Aug 2021.

Builds on

12 of 25 references.

References · 12

  1. 2020BLEURT: Learning Robust Metrics for Text Generationcited by 1,196
  2. 2019PlotQA: Reasoning over Scientific Plotscited by 317
  3. 2017FigureQA: An Annotated Figure Dataset for Visual Reasoningcited by 314
  4. 2017Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluationcited by 206
  5. 2018Data-to-Text Generation with Content Selection and Planningcited by 106
  6. 2020Chart-to-Text: Generating Natural Language Descriptions for Charts by Adapting the Transformer Modelcited by 77
  7. 2018RankME: Reliable Human Ratings for Natural Language Generationcited by 67
  8. 2019Data Extraction from Charts via Single Deep Neural Networkcited by 24
  9. 2018Chart-Text: A Fully Automated Chart Image Descriptorcited by 20
  10. 2017Beagle: Automated Extraction and Interpretation of Visualizations from the Webcited by 19
  11. 2019Learning to Select, Track, and Generate for Data-to-Textcited by 14
  12. 2017Scatteract: Automated extraction of data from scatter plotscited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 3; 2025: 3; 2026: 2.

12 papers.

  1. 2023ChartBench: A Benchmark for Complex Visual Reasoning in Chartscited by 116
  2. 2023ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short Summariescited by 30
  3. 2024Text2Chart31: Instruction Tuning for Chart Generation with Automatic Feedbackcited by 16
  4. 2023Summaries as Captions: Generating Figure Captions for Scientific Documents with Automated Text Summarizationcited by 14
  5. 2025ChartCap: Mitigating Hallucination of Dense Chart Captioningcited by 7
  6. 2023Tackling Hallucinations in Neural Chart Summarizationcited by 6
  7. 2024Faithful Chart Summarization with ChaTS-Picited by 5
  8. 2025Chart-HQA: A Benchmark for Hypothetical Question Answering in Chartscited by 5
  9. 2024AltChart: Enhancing VLM-based Chart Summarization Through Multi-Pretext Taskscited by 3
  10. 2025Structuring the Unstructured: A Systematic Review of Text-to-Structure Generation for Agentic AI with a Universal Evaluation Frameworkcited by 2
  11. 2026Multimodal Information Fusion for Chart Understanding: A Survey of MLLMs -- Evolution, Limitations, and Cognitive Enhancementcited by 1
  12. 2026Semantic Segmentation of Node and Edge Diagrams for Assistive Technologycited by 0