@inproceedings{singha-roy-mercer-2023-generating,
    title = "Generating Extractive and Abstractive Summaries in Parallel from Scientific Articles Incorporating Citing Statements",
    author = "Singha Roy, Sudipta  and
      Mercer, Robert E.",
    editor = "Dong, Yue  and
      Xiao, Wen  and
      Wang, Lu  and
      Liu, Fei  and
      Carenini, Giuseppe",
    booktitle = "Proceedings of the 4th New Frontiers in Summarization Workshop",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2023.newsum-1.8/",
    doi = "10.18653/v1/2023.newsum-1.8",
    pages = "75--86",
    abstract = "Summarization of scientific articles often overlooks insights from citing papers, focusing solely on the document`s content. To incorporate citation contexts, we develop a model to summarize a scientific document using the information in the source and citing documents. It concurrently generates abstractive and extractive summaries, each enhancing the other. The extractive summarizer utilizes a blend of heterogeneous graph-based neural networks and graph attention networks, while the abstractive summarizer employs an autoregressive decoder. These modules exchange control signals through the loss function, ensuring the creation of high-quality summaries in both styles."
}