LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models
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Cited by 24 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
Systems that support users in the automatic creation of visualizations must address several subtasks - understand the semantics of data, enumerate relevant visualization goals and generate visualization specifications. In this work, we pose visualization generation as a multi-stage generation problem and argue that well-orchestrated pipelines based on large language models (LLMs) such as ChatGPT/GPT-4 and image generation models (IGMs) are suitable to addressing these tasks. We present LIDA, a novel tool for generating grammar-agnostic visualizations and infographics. LIDA comprises of 4 modules - A SUMMARIZER that converts data into a rich but compact natural language summary, a GOAL EXPLORER that enumerates visualization goals given the data, a VISGENERATOR that generates, refines, executes and filters visualization code and an INFOGRAPHER module that yields data-faithful stylized graphics using IGMs. LIDA provides a python api, and a hybrid user interface (direct manipulation and multilingual natural language) for interactive chart, infographics and data story generation. Learn more about the project here - https://microsoft.github.io/lida/
Key facts. Cited by 82 papers in the map (data through 14 Oct 2026). Builds on 31 of its 48 references that are in the map. First posted on arXiv 6 Mar 2023.
Builds on
31 of 48 references.
References · 31
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- 2020NL4DV: A Toolkit for Generating Analytic Specifications for Data Visualization from Natural Language Queriescited by 74
- 2018Data2Vis: Automatic Generation of Data Visualizations Using Sequence to Sequence Recurrent Neural Networkscited by 48
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- 2019Sato: Contextual Semantic Type Detection in Tablescited by 3
- 2021User-Centric Semi-Automated Infographics Authoring and Recommendationcited by 2
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Citing papers per year: 2023: 7; 2024: 19; 2025: 32; 2026: 24.
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