Scene graphs are powerful representations that parse images into their abstract semantic
elements, ie, objects and their interactions, which facilitates visual comprehension and …

Recent developments in pre-trained neural language modeling have led to leaps in
accuracy on common-sense question-answering benchmarks. However, there is increasing …

Abstract Knowledge graphs (KGs) have become the preferred technology for representing,
sharing and adding knowledge to modern AI applications. While KGs have become a …

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

Commonsense reasoning systems should be able to generalize to diverse reasoning cases.
However, most state-of-the-art approaches depend on expensive data annotations and …

Wikidata and Wikipedia have been proven useful for reason-ing in natural language
applications, like question answering or entitylinking. Yet, no existing work has studied the …

Rapid development of autonomous vehicles has enabled the collection of huge amounts of
multimodal road traffic data resulting in large knowledge graphs for autonomous driving …

Challenges in Intelligent Traffic Monitoring (ITMo) are exacerbated by the large quantity and
modalities of data and the need for the utilization of state-of-the-art (SOTA) reasoners. We …

Aspect-based sentiment analysis (ABSA) endeavours predict the sentiment polarity of
specific aspects of a given review. Recently, prompt tuning has been widely explored and …

Stable Diffusion is a captivating text-to-image model that generates images based on text
input. However, a major challenge is that it is pretrained on a specific dataset, limiting its …