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Macro-Queries: An Exploration into Guided Chart Generation from High Level Prompts

2024-08-22 · Christopher J. Lee, Giorgio Tran, Roderick Tabalba, Jason Leigh, Ryan Longman

This paper explores the intersection of data visualization and Large Language Models (LLMs). Driven by the need to make a broader range of data visualization types accessible for novice users, we present a guided LLM-based pipeline designed to transform data, guided by high-level user questions (referred to as macro-queries), into a diverse set of useful visualizations. This approach leverages various prompting techniques, fine-tuning inspired by Abela's Chart Taxonomy, and integrated SQL tool usage.

📄 PDF Abstract BibTeX arXiv:2408.12726

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Data Visualization

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SET Dynamic Sparse Training method where weight mask is updated randomly periodically

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