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VisPilot uses multimodal prompts to enhance LLM visualization authoring

By PulseAugur Editorial · [1 sources] ·

Researchers have developed VisPilot, a system that uses multimodal prompts, combining text, sketches, and direct manipulation, to improve visualization authoring with large language models (LLMs). This approach addresses the limitations of text-only prompts, which can be imprecise and lead to misinterpretations. An empirical study found that multimodal prompts help users communicate spatial constraints and design preferences more effectively, maintaining similar task efficiency to text-only methods. The findings offer design implications for future human-AI authoring systems. AI

IMPACT Multimodal prompting could improve the precision and efficiency of AI-assisted design tools.

RANK_REASON The cluster contains an academic paper detailing a new system and empirical study. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

VisPilot uses multimodal prompts to enhance LLM visualization authoring

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The cluster contains an academic paper detailing a new system and empirical study. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zhen Wen, Luoxuan Weng, Yinghao Tang, Runjin Zhang, Yuxin Liu, Bo Pan, Minfeng Zhu, Wei Chen ·

    Exploring Multimodal Prompt for Visualization Authoring with Large Language Models

    arXiv:2504.13700v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have shown great potential in automating the process of visualization authoring through simple natural language utterances. However, instructing LLMs using natural language i…

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