mlsanityData to 7 Oct 2026

Automatic Claim Review for Climate Science via Explanation Generation

arXiv 2107.14740 ↗First posted 30 Jul 2021cs.CLcited by 4

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Abstract (arXiv)

There is unison is the scientific community about human induced climate change. Despite this, we see the web awash with claims around climate change scepticism, thus driving the need for fact checking them but at the same time providing an explanation and justification for the fact check. Scientists and experts have been trying to address it by providing manually written feedback for these claims. In this paper, we try to aid them by automating generating explanation for a predicted veracity label for a claim by deploying the approach used in open domain question answering of a fusion in decoder augmented with retrieved supporting passages from an external knowledge. We experiment with different knowledge sources, retrievers, retriever depths and demonstrate that even a small number of high quality manually written explanations can help us in generating good explanations.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 22 of its 45 references that are in the map. First posted on arXiv 30 Jul 2021.

Builds on

22 of 45 references.

References · 22

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10 more
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Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 3.

4 papers.

  1. 2024Generative Large Language Models in Automated Fact-Checking: A Surveycited by 19
  2. 2021The Choice of Knowledge Base in Automated Claim Checkingcited by 1
  3. 2024Generative Debunking of Climate Misinformationcited by 1
  4. 2024Science Checker Reloaded: A Bidirectional Paradigm for Transparency and Logical Reasoningcited by 0