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LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models

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arxiv 2303.02927 v3 pith:V2FWEA6B submitted 2023-03-06 cs.AI cs.HCcs.PL

classification cs.AIcs.HCcs.PL
keywords generationlidavisualizationdatalanguageinfographicsmodelsvisualizations
verification ladder T0 review T1 audit T2 compute T3 formal
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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/

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. ProactiveVA: Proactive Visual Analytics with LLM-Based UI Agent

    cs.HC 2025-07 conditional novelty 6.0 of 10

    An LLM-based UI agent monitors visual analytics interactions, detects when users struggle, infers their intent, and proactively provides context-aware guidance.

  2. Data-to-Dashboard: Multi-Agent LLM Framework for Insightful Visualization in Enterprise Analytics

    cs.AI 2025-05 conditional novelty 5.0 of 10

    A multi-agent LLM system that detects the business domain of a raw dataset, generates domain-grounded insights, and renders them as charts, claims to beat single-prompt GPT-4o in insight quality.

  3. GeoPandas-AI: A Smart Class Bringing LLM as Stateful AI Code Assistant

    cs.HC 2025-06 conditional novelty 4.0 of 10

    A new open-source Python class, GeoDataFrameAI, adds a stateful LLM chat interface directly to GeoPandas data frames for geospatial code generation and analysis.

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