@inproceedings{shinde-etal-2022-extractive,
    title = "An Extractive-Abstractive Approach for Multi-document Summarization of Scientific Articles for Literature Review",
    author = "Shinde, Kartik  and
      Roy, Trinita  and
      Ghosal, Tirthankar",
    editor = "Cohan, Arman  and
      Feigenblat, Guy  and
      Freitag, Dayne  and
      Ghosal, Tirthankar  and
      Herrmannova, Drahomira  and
      Knoth, Petr  and
      Lo, Kyle  and
      Mayr, Philipp  and
      Shmueli-Scheuer, Michal  and
      de Waard, Anita  and
      Wang, Lucy Lu",
    booktitle = "Proceedings of the Third Workshop on Scholarly Document Processing",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2022.sdp-1.25/",
    pages = "204--209",
    abstract = "Research in the biomedical domain is con- stantly challenged by its large amount of ever- evolving textual information. Biomedical re- searchers are usually required to conduct a lit- erature review before any medical interven- tion to assess the effectiveness of the con- cerned research. However, the process is time- consuming, and therefore, automation to some extent would help reduce the accompanying information overload. Multi-document sum- marization of scientific articles for literature reviews is one approximation of such automa- tion. Here in this paper, we describe our pipelined approach for the aforementioned task. We design a BERT-based extractive method followed by a BigBird PEGASUS-based ab- stractive pipeline for generating literature re- view summaries from the abstracts of biomedi- cal trial reports as part of the Multi-document Summarization for Literature Review (MSLR) shared task1 in the Scholarly Document Pro- cessing (SDP) workshop 20222. Our proposed model achieves the best performance on the MSLR-Cochrane leaderboard3 on majority of the evaluation metrics. Human scrutiny of our automatically generated summaries indicates that our approach is promising to yield readable multi-article summaries for conducting such lit- erature reviews."
}