@inproceedings{chen-etal-2020-corpus,
    title = "A Corpus of Very Short Scientific Summaries",
    author = "Chen, Yifan  and
      Polajnar, Tamara  and
      Batchelor, Colin  and
      Teufel, Simone",
    editor = "Fern{\'a}ndez, Raquel  and
      Linzen, Tal",
    booktitle = "Proceedings of the 24th Conference on Computational Natural Language Learning",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2020.conll-1.12/",
    doi = "10.18653/v1/2020.conll-1.12",
    pages = "153--164",
    abstract = "We present a new summarisation task, taking scientific articles and producing journal table-of-contents entries in the chemistry domain. These are one- or two-sentence author-written summaries that present the key findings of a paper. This is a first look at this summarisation task with an open access publication corpus consisting of titles and abstracts, as input texts, and short author-written advertising blurbs, as the ground truth. We introduce the dataset and evaluate it with state-of-the-art summarisation methods."
}