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

Ronald Cardenas, Bingsheng Yao, Dakuo Wang, Yufang Hou
10/23/2023
cs.CL

No official code found. Best implementation: ronaldahmed/scitechnews (5 stars, last commit 2023-10-24).

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.

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Code Implementations(1)

Repository with dataset and code to reproduce results in {‘Don’t Get Too Technical with Me’: A Discourse Structure-Based Framework for Science Journalism}

50Shell, PythonOct 8, 20232 years ago

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Cite this paper

@article{cardenas2023dont,
  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},
  year   = {2023},
  eprint = {2310.15077},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.15077v1}
}

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