In recent years, we saw the emergence of several approaches for producing machine-
readable, semantically rich, interlinked description of the content of research publications …

In recent years, transformer-based models have emerged as powerful tools for natural
language processing tasks, demonstrating remarkable performance in several domains …

With the most advanced natural language processing and artificial intelligence approaches,
effective summarization of long and multi-topic documents—such as academic papers—for …

As scientific literature has grown exponentially, researchers often rely on paper triaging
strategies such as browsing abstracts before deciding to delve into a paper's full text …

Keeping up with the research literature plays an important role in the workflow of scientists–
allowing them to understand a field, formulate the problems they focus on, and develop the …

Academia and industry share a complex, multifaceted, and symbiotic relationship. Analyzing
the knowledge flow between them, understanding which directions have the biggest …

Classifying scientific articles, patents, and other documents according to the relevant
research topics is an important task, which enables a variety of functionalities, such as …

Machine Learning (ML) has been widely used in Natural Language Processing (NLP)
applications. A fundamental assumption in ML is that training data and real-world data …

The ecology of thermoplastic materials is rapidly evolving, enabling an exciting landscape of
functional, aesthetic, and interactive forms. Despite their utility in fused filament fabrication …

Communities of practice (CoPs) play a crucial role in cross-pollination and learning within
various skill-based and craft domains. These communities often share common materials …