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  1. Home
  3. Encqa: Benchmarking Vision-language Models On Visual Encodings For Charts.
  1. Home
  3. Encqa: Benchmarking Vision-language Models On Visual Encodings For Charts.

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EncQA: Benchmarking Vision-Language Models on Visual Encodings for Charts.

Kushin Mukherjee, Donghao Ren, Dominik Moritz

    IEEE Transactions on Visualization and Computer Graphics
    |November 20, 2025

    View abstract on PubMed

    Summary
    This summary is machine-generated.

    Vision-language models (VLMs) struggle with chart interpretation despite high scores. A new benchmark, ENCQA, reveals performance gaps in visual reasoning, suggesting targeted strategies are needed over just scaling models.

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    Area of Science:

    • Computer Science
    • Artificial Intelligence
    • Data Visualization

    Background:

    • Multimodal vision-language models (VLMs) show increasing performance on chart understanding tasks.
    • Current benchmarks may not fully assess the visual reasoning required for comprehensive chart interpretation.

    Purpose of the Study:

    • Introduce ENCQA, a novel benchmark for evaluating visual reasoning in chart understanding.
    • Systematically assess VLM capabilities across diverse visual encodings and analytical tasks.

    Main Methods:

    • Developed ENCQA with 2,076 synthetic question-answer pairs.
    • Covered six visual encoding channels (position, length, area, color quantitative, color nominal, shape).
    • Included eight analytical tasks (e.g., find extrema, retrieve value, correlate values).

    Main Results:

    • Evaluated 9 state-of-the-art VLMs on the ENCQA benchmark.
    • Observed significant performance variations across different encodings and tasks.
    • Found no consistent performance improvement with increased model size for many task-encoding combinations.

    Conclusions:

    • Current VLMs have specific visual reasoning gaps in chart understanding.
    • Advancing chart interpretation requires targeted improvements beyond scaling model or dataset size.
    • ENCQA provides a framework for identifying and addressing these specific visual reasoning deficiencies.