Summary of Scinews: From Scholarly Complexities to Public Narratives — a Dataset For Scientific News Report Generation, by Dongqi Liu et al.
SciNews: From Scholarly Complexities to Public Narratives – A Dataset for Scientific News Report Generation
by Dongqi Liu, Yifan Wang, Jia Loy, Vera Demberg
First submitted to arxiv on: 26 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a new corpus for generating scientific news reports that can enhance the accessibility of scholarly insights. The corpus consists of parallel publications and their corresponding news reports across nine disciplines. To demonstrate the utility and reliability of this dataset, an analysis is conducted highlighting divergences in readability and brevity between news narratives and academic manuscripts. State-of-the-art text generation models are employed for benchmarking, with both automatic and human evaluation used to lay the groundwork for future explorations into automated scientific news report generation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a new way to make research more accessible by collecting academic papers and their corresponding news reports across nine areas of study. To show that this dataset works well, the authors compare how readable and concise the news stories are compared to the original research papers. They use advanced language models to test this dataset and get feedback from both machines and humans. This work sets the stage for developing ways to automatically create news articles about scientific discoveries. |
Keywords
» Artificial intelligence » Text generation
