Creating written products is essential to modern life, including writings about one's identity and personal experiences. However, writing is often a difficult activity that requires extensive effort to frame the central ideas, the pursued approach to communicate the central ideas, e.g., using analogies, metaphors, or other possible means, the needed presentation structure, and the actual verbal expression. Large Language Models, a recently emerged approach in Machine Learning, can offer a significant help in reducing the effort and improving the quality of written products. This paper proposes a new computational approach to explore prompts that given as inputs to a Large Language Models can generate cues to improve the considered written products. Two case studies on improving write-ups, one based on an analogy and one on a metaphor, are also presented in the paper.

翻译：创作书面作品是现代生活的重要组成部分，包括关于个人身份和经历的写作。然而，写作往往是一项困难的活动，需要付出大量努力来构思核心思想、传达核心思想所采用的方法（例如使用类比、隐喻或其他可能手段）、所需的呈现结构以及实际的文字表达。大型语言模型作为机器学习领域新兴的一种方法，可以显著帮助减少写作工作量并提高书面作品质量。本文提出了一种新的计算方法，用于探索输入到大型语言模型的提示词，以生成改进所考虑书面作品的线索。本文还介绍了两个改进写作的案例研究，一个基于类比，另一个基于隐喻。