@inproceedings{elsahar-etal-2021-self,
    title = "Self-Supervised and Controlled Multi-Document Opinion Summarization",
    author = "Elsahar, Hady  and
      Coavoux, Maximin  and
      Rozen, Jos  and
      Gall{\'e}, Matthias",
    editor = "Merlo, Paola  and
      Tiedemann, Jorg  and
      Tsarfaty, Reut",
    booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume",
    month = apr,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2021.eacl-main.141/",
    doi = "10.18653/v1/2021.eacl-main.141",
    pages = "1646--1662",
    abstract = "We address the problem of unsupervised abstractive summarization of collections of user generated reviews through self-supervision and control. We propose a self-supervised setup that considers an individual document as a target summary for a set of similar documents. This setting makes training simpler than previous approaches by relying only on standard log-likelihood loss and mainstream models. We address the problem of hallucinations through the use of control codes, to steer the generation towards more coherent and relevant summaries."
}