论文标题
气候狂热：用于验证现实世界气候索赔的数据集
CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims
论文作者
论文摘要
我们介绍了气候伴随，这是一种新的公开可用数据集，用于验证与气候变化有关的索赔。通过为研究界提供数据集，我们旨在促进和鼓励改善算法以检索特定于气候特定主张的证据支持，应对基本语言理解挑战的证据支持，并最终帮助减轻误解对气候变化的影响。我们将发烧的方法[1]（人为设计的主张的最大数据集）改编成从互联网收集的现实生活中。在此过程中，我们可以依靠著名的气候科学家的专业知识，但事实证明这绝非易事。我们讨论了在\ textsc {fever}框架内建模现实世界中与气候相关的主张的惊人，微妙的复杂性，我们认为这为一般的自然语言理解提供了宝贵的挑战。我们希望我们的工作能够标志着气候科学和AI社区的新令人兴奋的长期共同努力的开始。
We introduce CLIMATE-FEVER, a new publicly available dataset for verification of climate change-related claims. By providing a dataset for the research community, we aim to facilitate and encourage work on improving algorithms for retrieving evidential support for climate-specific claims, addressing the underlying language understanding challenges, and ultimately help alleviate the impact of misinformation on climate change. We adapt the methodology of FEVER [1], the largest dataset of artificially designed claims, to real-life claims collected from the Internet. While during this process, we could rely on the expertise of renowned climate scientists, it turned out to be no easy task. We discuss the surprising, subtle complexity of modeling real-world climate-related claims within the \textsc{fever} framework, which we believe provides a valuable challenge for general natural language understanding. We hope that our work will mark the beginning of a new exciting long-term joint effort by the climate science and AI community.
