Recent advancements in large language models have revolutionized information access, as these models harness data available on the web to address complex queries, becoming the preferred information source for many users. In certain cases, queries are about publicly available data, which can be effectively answered with data visualizations. In this paper, we investigate the ability of large language models to provide accurate data and relevant visualizations in response to such queries. Specifically, we investigate the ability of GPT-3 and GPT-4 to generate visualizations with dataless prompts, where no data accompanies the query. We evaluate the results of the models by comparing them to visualization cheat sheets created by visualization experts.

翻译：近年来，大型语言模型的突破性进展彻底改变了信息获取方式。这些模型能够利用网络上的可用数据来处理复杂查询，已成为众多用户首选的信息来源。在某些情况下，查询涉及公开可用的数据，这类问题通过数据可视化可以更有效地解答。本文研究了大型语言模型在响应此类查询时提供准确数据和相关可视化图表的能力。具体而言，我们探究了GPT-3和GPT-4在无数据提示（即查询不附带任何数据）条件下生成可视化图表的能力。我们通过将模型生成的结果与可视化专家创建的可视化速查表进行对比，对模型表现进行了评估。