IdeaReader: A Machine Reading System for Understanding the Idea Flow of Scientific Publications

@article{Li2022IdeaReaderAM,
  title={IdeaReader: A Machine Reading System for Understanding the Idea Flow of Scientific Publications},
  author={Qi Li and Yuyang Ren and Xingli Wang and Luoyi Fu and Jiaxin Ding and Xinde Cao and Xinbing Wang and Cheng Zhou},
  journal={ArXiv},
  year={2022},
  volume={abs/2209.13243}
}
Understanding the origin and influence of the publication’s idea is critical to conducting scientific research. However, the proliferation of scientific publications makes it difficult for researchers to sort out the evolution of all relevant literature. To this end, we present IdeaReader, a machine reading system that finds out which papers are most likely to inspire or be influenced by the target publication and summarizes the ideas of these papers in natural language. Specifically, IdeaReader first… 
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