English

'Don't Get Too Technical with Me': A Discourse Structure-Based Framework for Science Journalism

Computation and Language 2023-10-24 v1

Abstract

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.

Keywords

Cite

@article{arxiv.2310.15077,
  title  = {'Don't Get Too Technical with Me': A Discourse Structure-Based Framework for Science Journalism},
  author = {Ronald Cardenas and Bingsheng Yao and Dakuo Wang and Yufang Hou},
  journal= {arXiv preprint arXiv:2310.15077},
  year   = {2023}
}

Comments

Accepted to EMNLP 2023

R2 v1 2026-06-28T12:59:11.211Z