More than one hundred benchmarks have been developed to test the commonsense
knowledge and commonsense reasoning abilities of artificial intelligence (AI) systems …

As online false information continues to grow, automated fact‐checking has gained an
increasing amount of attention in recent years. Researchers in the field of Natural Language …

Reasoning, as an essential ability for complex problem-solving, can provide back-end
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …

Automatic KB completion for commonsense knowledge graphs (eg, ATOMIC and
ConceptNet) poses unique challenges compared to the much studied conventional …

Machine Reading Comprehension (MRC) is a challenging Natural Language Processing
(NLP) research field with wide real-world applications. The great progress of this field in …

Causal inference has shown potential in enhancing the predictive accuracy, fairness,
robustness, and explainability of Natural Language Processing (NLP) models by capturing …

The proliferation of social media has promoted the spread of misinformation that raises
many concerns in our society. This paper focuses on a critical problem of explainable …

Commonsense knowledge is essential for many AI applications, including those in natural
language processing, visual processing, and planning. Consequently, many sources that …

Commonsense knowledge, such as knowing that “bumping into people annoys them” or
“rain makes the road slippery”, helps humans navigate everyday situations seamlessly. Yet …

Commonsense question answering (QA) requires background knowledge which is not
explicitly stated in a given context. Prior works use commonsense knowledge graphs (KGs) …