What Happened to Automated Visualization? An Agentic Analysis
Year: 2025
Type: conference-paper
Abstract: Recently, foundation models, particularly large language models (LLMs), have shown great capabilities across a wide variety of tasks that were previously done by human, such as code generation and analytic reasoning. Such advances open new possibilities for further automating the data analysis process. This technical report presents the AgenticInsight system developed for the Agentic VIS Challenge 2025.AgenticInsight is an automated system that uses an agentic workflow to generate insights and visualizations from a given dataset. The agentic workflow is designed on the basis of a conceptual framework adapted from the visual analytics process model. Powered by the LLMs, the agent automates the essential steps in the visual analytics workflow, including planning, data transformation, visualization generation, analysis code generation, and knowledge extraction. Our workflow is designed to be generalizable and not tailored to a specific dataset. Meanwhile, it allows human users to specify high-level intentions, preferences, and domain knowledge in a separate configuration file, which is incorporated to guide the analytical process. As a result, our workflow can be applied to a range of analysis questions and domains. This report details the system design and decisions, demonstrates the system’s performance and generalizability, and presents reflections on building an automated LLM-powered analysis system.
Authors: Meng, Weiyao, Guo, Yuhan, Xie, Zefei, Xu, Kai
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7113809036
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