@inproceedings{xing-etal-2022-automatic,
    title = "Automatic Explanation Generation For Climate Science Claims",
    author = "Xing, Rui  and
      Bhatia, Shraey  and
      Baldwin, Timothy  and
      Lau, Jey Han",
    editor = "Parameswaran, Pradeesh  and
      Biggs, Jennifer  and
      Powers, David",
    booktitle = "Proceedings of the 20th Annual Workshop of the Australasian Language Technology Association",
    month = dec,
    year = "2022",
    address = "Adelaide, Australia",
    publisher = "Australasian Language Technology Association",
    url = "https://preview.aclanthology.org/Author-page-Marten-During-lu/2022.alta-1.16/",
    pages = "122--129",
    abstract = "Climate change is an existential threat to humanity, the proliferation of unsubstantiated claims relating to climate science is manipulating public perception, motivating the need for fact-checking in climate science. In this work, we draw on recent work that uses retrieval-augmented generation for veracity prediction and explanation generation, in framing explanation generation as a query-focused multi-document summarization task. We adapt PRIMERA to the climate science domain by adding additional global attention on claims. Through automatic evaluation and qualitative analysis, we demonstrate that our method is effective at generating explanations."
}