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Visualizationary: Automating Design Feedback for Visualization Designers Using Large Language Models

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PRE
AI
S
Sungbok Shin
S
Sanghyun Hong
N
Niklas Elmqvist
DOI：10.1109/TVCG.2025.3579700delete
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摘要

摘要

En 中文
交互式可视化编辑器使用户能够无需编写代码即可创建可视化，但并未提供关于有效视觉传达的艺术与技巧的指导。本文探讨了使用现成的大型语言模型（LLMs）为可视化设计师提供可操作且定制化反馈的潜力。我们的实现——Visualizationary，通过两个关键组件展示了如何利用ChatGPT实现这一目的：一是可视化设计指南的引言，二是提取可视化图像中显著指标的感知过滤器套件。我们呈现了一项纵向用户研究的发现，该研究涉及13名可视化设计师——6名新手、4名中级和3名专家，他们在数天内从零开始创建新的可视化。我们的结果表明，通过大型语言模型以自然语言提供指导，能够帮助经验丰富的设计师优化其可视化作品。
Keyword:
Visualization design
design critique
feedback
human-centered AI
large language models

期刊

IEEE Transactions on Visualization and Computer Graphics 封面图
IEEE Transactions on Visualization and Computer Graphics
IF:
6.5
论文数:
403
被引数:
2.2W

机构

A
Aarhus University
学者数:
4.3W
论文数: 4.2W
被引数: 4.8W
O
Oregon State University
学者数:
1.7W
论文数: 1.5W
被引数: 2.4W
U
université paris-saclay
学者数:
2.2K
论文数: 898
被引数: 1
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