@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://aclanthology.org/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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Automatic Explanation Generation For Climate Science Claims
%A Xing, Rui
%A Bhatia, Shraey
%A Baldwin, Timothy
%A Lau, Jey Han
%Y Parameswaran, Pradeesh
%Y Biggs, Jennifer
%Y Powers, David
%S Proceedings of the 20th Annual Workshop of the Australasian Language Technology Association
%D 2022
%8 December
%I Australasian Language Technology Association
%C Adelaide, Australia
%F xing-etal-2022-automatic
%X 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.
%U https://aclanthology.org/2022.alta-1.16
%P 122-129
Markdown (Informal)
[Automatic Explanation Generation For Climate Science Claims](https://aclanthology.org/2022.alta-1.16) (Xing et al., ALTA 2022)
ACL
- Rui Xing, Shraey Bhatia, Timothy Baldwin, and Jey Han Lau. 2022. Automatic Explanation Generation For Climate Science Claims. In Proceedings of the 20th Annual Workshop of the Australasian Language Technology Association, pages 122–129, Adelaide, Australia. Australasian Language Technology Association.