The number of scientific publications in the literature is steadily growing, containing our
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …

Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two
hitherto distinct approaches.” Neuro” refers to the artificial neural networks prominent in …

Large language models (LLMs), such as GPT-4, are revolutionizing software's ability to
understand, process, and synthesize language. The authors of this paper believe that this …

This paper develops a novel framework for semantic image retrieval based on the notion of
a scene graph. Our scene graphs represent objects (" man"," boat"), attributes of objects (" …

We provide a comprehensive survey of the research literature that applies Information
Extraction techniques in a Semantic Web setting. Works in the intersection of these two …

Weak supervision is a popular method for building machine learning models without relying
on ground truth annotations. Instead, it generates probabilistic training labels by estimating …

The exponential growth of scientific literature–which we call the 'big literature'phenomenon–
has created great challenges in literature comprehension and synthesis. The traditional …

Machine Learning has been the quintessential solution for many AI problems, but learning is
still heavily dependent on the specific training data. Some learning models can be …

Ground is an open-source data context service, a system to manage all the information that
informs the use of data. Data usage has changed both philosophically and practically in the …

Nowadays, most openly available knowledge bases (KBs) are incomplete, since they are
not synchronized with the emerging facts happening in the real world. Therefore, knowledge …