Creating compelling captions for data visualizations has been a longstanding challenge. Visualization researchers are typically untrained in journalistic reporting and hence the captions that are placed below data visualizations tend to be not overly engaging and rather just stick to basic observations about the data. In this work we explore the opportunities offered by the newly emerging crop of large language models (LLM) which use sophisticated deep learning technology to produce human-like prose. We ask, can these powerful software devices be purposed to produce engaging captions for generic data visualizations like a scatterplot. It turns out that the key challenge lies in designing the most effective prompt for the LLM, a task called prompt engineering. We report on first experiments using the popular LLM GPT-3 and deliver some promising results.
翻译:为数据可视化创建令人信服的字幕是一个长期的挑战。 视觉化研究人员通常在新闻报道方面没有受过训练,因此,在数据可视化下面的字幕往往不会过于吸引人,而只是坚持对数据的基本观察。 在这项工作中,我们探索新兴的大型语言模型(LLM)提供的机会,这些模型利用先进的深层次学习技术制作人文流传。我们问,这些强大的软件设备是否可以用来制作通用数据可视化的引人入胜的字幕,如散射图。我们发现,关键的挑战在于设计最有效的LLM(即所谓的即时工程 ) ( LLMM GPT-3) 。我们报告使用流行的LLMM GPT-3(GPT-3) 进行的初步实验,并拿出一些有希望的结果。