Sources of commonsense knowledge support applications in natural language
understanding, computer vision, and knowledge graphs. Given their complementarity, their …

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

Conceptualization, or viewing entities and situations as instances of abstract concepts in
mind and making inferences based on that, is a vital component in human intelligence for …

Scene graph generation (SGG) models seek to detect relationships between objects in a
given image. One challenge in this area is the biased distribution of predicates in the dataset …

Commonsense knowledge (CSK) about concepts and their properties is helpful for AI
applications. Prior works, such as ConceptNet, have compiled large CSK collections …

Commonsense knowledge (CSK) about concepts and their properties is useful for AI
applications such as robust chatbots. Prior works like ConceptNet, TupleKB and others …

Commonsense knowledge is a foundational cornerstone of artificial intelligence
applications. Whereas information extraction and knowledge base construction for instance …

Media technologies now provide facts, answers, and “knowledge” to people–search
engines, apps, and virtual assistants increasingly articulate responses rather than direct …

This chapter illustrates how suitable neuro-symbolic models for language understanding
can enable domain generalizability and robustness in downstream tasks. Different methods …

Robust estimation of concept similarity is crucial for applications of AI in the commercial,
biomedical, and publishing domains, among others. While the related task of word similarity …