@inproceedings{jain-etal-2022-comparative,
    title = "Comparative Snippet Generation",
    author = "Jain, Saurabh  and
      Miao, Yisong  and
      Kan, Min-Yen",
    editor = "Malmasi, Shervin  and
      Rokhlenko, Oleg  and
      Ueffing, Nicola  and
      Guy, Ido  and
      Agichtein, Eugene  and
      Kallumadi, Surya",
    booktitle = "Proceedings of the Fifth Workshop on e-Commerce and NLP (ECNLP 5)",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.ecnlp-1.7/",
    doi = "10.18653/v1/2022.ecnlp-1.7",
    pages = "49--57",
    abstract = "We model products' reviews to generate comparative responses consisting of positive and negative experiences regarding the product. Specifically, we generate a single-sentence, comparative response from a given positive and a negative opinion. We contribute the first dataset for this task of Comparative Snippet Generation from contrasting opinions regarding a product, and an analysis of performance of a pre-trained BERT model to generate such snippets."
}