Chart Question Answering

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

3 leaderboard tables shown for this task, 3 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

9 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

25 shown of 25 papers with code (50 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding
  7 Oct 2022 4 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  Visually-situated language is ubiquitous -- sources range from textbooks with diagrams to web pages with images and tables, to mobile apps with buttons and forms.
• StructChart: On the Schema, Metric, and Augmentation for Visual Chart Understanding
  20 Sep 2023 3 repositories listed
  Specifically, StructChart first reformulates the chart data from the tubular form (linearized CSV) to STR, which can friendlily reduce the task gap between chart perception and reasoning.
• ScreenAI: A Vision-Language Model for UI and Infographics Understanding
  7 Feb 2024 2 repositories listed
  At the heart of this mixture is a novel screen annotation task in which the model has to identify the type and location of UI elements.
• Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
  24 Aug 2023 2 repositories listed Syntology ran 0 of 2 samples · 2 unverified · 2 pointer-only (licence)
  In this work, we introduce the Qwen-VL series, a set of large-scale vision-language models (LVLMs) designed to perceive and understand both texts and images.
• PaLI-X: On Scaling up a Multilingual Vision and Language Model
  29 May 2023 2 repositories listed Syntology ran 6 of 7 samples · 1 unverified
  We present the training recipe and results of scaling up PaLI-X, a multilingual vision and language model, both in terms of size of the components and the breadth of its training task mixture.
• ChartCards: A Chart-Metadata Generation Framework for Multi-Task Chart Understanding
  21 May 2025 1 repository listed
  The emergence of Multi-modal Large Language Models (MLLMs) presents new opportunities for chart understanding.
• Judging the Judges: Can Large Vision-Language Models Fairly Evaluate Chart Comprehension and Reasoning?
  13 May 2025 1 repository listed
  While using LVLMs as judges to assess the chart comprehension capabilities of other LVLMs could streamline evaluation processes, challenges like proprietary datasets, restricted access to powerful models, and evaluation…
• ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering
  7 Apr 2025 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  Charts are ubiquitous, as people often use them to analyze data, answer questions, and discover critical insights.
• RefChartQA: Grounding Visual Answer on Chart Images through Instruction Tuning
  29 Mar 2025 1 repository listed
  To bridge this gap, we introduce RefChartQA, a novel benchmark that integrates Chart Question Answering (ChartQA) with visual grounding, enabling models to refer elements at multiple granularities within chart images.
• SBS Figures: Pre-training Figure QA from Stage-by-Stage Synthesized Images
  23 Dec 2024 1 repository listed
  Our SBSFigures demonstrate a strong pre-training effect, making it possible to achieve efficient training with a limited amount of real-world chart data starting from our pre-trained weights.
• VProChart: Answering Chart Question through Visual Perception Alignment Agent and Programmatic Solution Reasoning
  3 Sep 2024 1 repository listed
  Charts are widely used for data visualization across various fields, including education, research, and business.
• MSG-Chart: Multimodal Scene Graph for ChartQA
  9 Aug 2024 1 repository listed
  Automatic Chart Question Answering (ChartQA) is challenging due to the complex distribution of chart elements with patterns of the underlying data not explicitly displayed in charts.
• Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction Tuning
  29 Jul 2024 1 repository listed
  To fill the gap, we propose a visualization-referenced instruction tuning approach to guide the training dataset enhancement and model development.
• SIMPLOT: Enhancing Chart Question Answering by Distilling Essentials
  22 Feb 2024 1 repository listed
  Recently, interpreting complex charts with logical reasoning has emerged as challenges due to the development of vision-language models.
• DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense Understanding
  29 Oct 2023 1 repository listed
  Our DCQA dataset is expected to foster research on understanding visualizations in documents, especially for scenarios that require complex reasoning for charts in the visually-rich document.
• PaLI-3 Vision Language Models: Smaller, Faster, Stronger
  13 Oct 2023 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  This paper presents PaLI-3, a smaller, faster, and stronger vision language model (VLM) that compares favorably to similar models that are 10x larger.
• RealCQA: Scientific Chart Question Answering as a Test-bed for First-Order Logic
  3 Aug 2023 1 repository listed
  We present a comprehensive study of chart visual question-answering(QA) task, to address the challenges faced in comprehending and extracting data from chart visualizations within documents.
• UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning
  24 May 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Charts are very popular for analyzing data, visualizing key insights and answering complex reasoning questions about data.
• DePlot: One-shot visual language reasoning by plot-to-table translation
  20 Dec 2022 1 repository listed
  Compared with a SOTA model finetuned on more than >28k data points, DePlot+LLM with just one-shot prompting achieves a 24.
• MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering
  19 Dec 2022 1 repository listed
  Visual language data such as plots, charts, and infographics are ubiquitous in the human world.
• ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning
  19 Mar 2022 1 repository listed
  To address the unique challenges in our benchmark involving visual and logical reasoning over charts, we present two transformer-based models that combine visual features and the data table of the chart in a unified way…
• Classification-Regression for Chart Comprehension
  29 Nov 2021 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Our model is particularly well suited for realistic questions with out-of-vocabulary answers that require regression.
• Answering Questions about Data Visualizations using Efficient Bimodal Fusion
  5 Aug 2019 1 repository listed
  Chart question answering (CQA) is a newly proposed visual question answering (VQA) task where an algorithm must answer questions about data visualizations, e.
• DVQA: Understanding Data Visualizations via Question Answering
  24 Jan 2018 1 repository listed
  Bar charts are an effective way to convey numeric information, but today's algorithms cannot parse them.
• FigureQA: An Annotated Figure Dataset for Visual Reasoning
  19 Oct 2017 1 repository listed Syntology ran 0 of 12 samples · 12 unverified · 12 pointer-only (licence)
  To resolve, such questions often require reference to multiple plot elements and synthesis of information distributed spatially throughout a figure.

Syntology lines on 8 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.