'Don't Get Too Technical with Me': A Discourse Structure-Based Framework
  for Science Journalism
Ronald Cardenas Bingsheng Yao Dakuo Wang Yufang Hou
Science journalism refers to the task of reporting technical findings of a
scientific paper as a less technical news article to the general public
audience. We aim to design an automated system to support this real-world task
(i.e., automatic science journalism) by 1) introducing a newly-constructed and
real-world dataset (SciTechNews), with tuples of a publicly-available
scientific paper, its corresponding news article, and an expert-written short
summary snippet; 2) proposing a novel technical framework that integrates a
paper's discourse structure with its metadata to guide generation; and, 3)
demonstrating with extensive automatic and human experiments that our framework
outperforms other baseline methods (e.g. Alpaca and ChatGPT) in elaborating a
content plan meaningful for the target audience, simplifying the information
selected, and producing a coherent final report in a layman's style.