We propose the LLMs4OL approach, which utilizes Large Language Models (L...
There have been many recent investigations into prompt-based training of...
The rapid growth of research publications has placed great demands on di...
We present a large-scale empirical investigation of the zero-shot learni...
When semantically describing knowledge graphs (KGs), users have to make ...
We are faced with an unprecedented production in scholarly publications
...
Domain-specific named entity recognition (NER) on Computer Science (CS)
...
Biological data and knowledge bases increasingly rely on Semantic Web
te...
In multiple-choice exams, students select one answer from among typicall...
We describe a rule-based approach for the automatic acquisition of salie...
With the rapid growth of research publications, empowering scientists to...
There is currently a gap between the natural language expression of scho...
The Eigenfactor is a journal metric, which was developed by Bergstrom an...
Purpose: The aim of this work is to normalize the NLPCONTRIBUTIONS schem...
In the biotechnology and biomedical domains, recent text mining efforts
...
As a novel contribution to the problem of semantifying biological assays...
We describe an annotation initiative to capture the scholarly contributi...
With the rapid growth of research publications, there is a vast amount o...
We introduce the STEM (Science, Technology, Engineering, and Medicine)
D...
We examine the novel task of domain-independent scientific concept extra...
Despite improved digital access to scholarly knowledge in recent decades...