@inproceedings{guan-padmakumar-2023-extract,
    title = "Extract, Select and Rewrite: A Modular Sentence Summarization Method",
    author = "Guan, Shuo  and
      Padmakumar, Vishakh",
    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/jlcl-multiple-ingestion/2023.newsum-1.4/",
    doi = "10.18653/v1/2023.newsum-1.4",
    pages = "41--48",
    abstract = "A modular approach has the advantage of being compositional and controllable, comparing to most end-to-end models. In this paper we propose Extract-Select-Rewrite (ESR), a three-phase abstractive sentence summarization method. We decompose summarization into three stages: (i) knowledge extraction, where we extract relation triples from the text using off-the-shelf tools; (ii) content selection, where a subset of triples are selected; and (iii) rewriting, where the selected triple are realized into natural language. Our results demonstrates that ESR is competitive with the best end-to-end models while being more faithful. {\%}than these baseline models. Being modular, ESR`s modules can be trained on separate data which is beneficial in low-resource settings and enhancing the style controllability on text generation."
}