Commonsense fact verification, as a challenging branch of commonsense question-answering (QA), aims to verify through facts whether a given commonsense claim is correct or not. Answering commonsense questions necessitates a combination of knowledge from various levels. However, existing studies primarily rest on grasping either unstructured evidence or potential reasoning paths from structured knowledge bases, yet failing to exploit the benefits of heterogeneous knowledge simultaneously. In light of this, we propose Decker, a commonsense fact verification model that is capable of bridging heterogeneous knowledge by uncovering latent relationships between structured and unstructured knowledge. Experimental results on two commonsense fact verification benchmark datasets, CSQA2.0 and CREAK demonstrate the effectiveness of our Decker and further analysis verifies its capability to seize more precious information through reasoning.

Decker是一种应用于常识事实验证的模型，它可以通过发现结构化和非结构化知识之间的潜在关系，实现异构知识的桥接，并实现更精确的理解和推理。实验结果表明，Decker在两个常识事实验证基准数据集上表现出很高的准确性和能力。

Decker：用异构知识进行常识事实验证的双重检查