With Artificial Intelligence (AI) increasingly permeating various aspects of society, including
healthcare, the adoption of the Transformers neural network architecture is rapidly changing …

The latest batch of research has equipped language models with the ability to attend over
relevant and factual information from non-parametric external sources, drawing a …

Text mining in the optical-materials domain is becoming increasingly important as the
number of scientific publications in this area grows rapidly. Language models such as …

Although gold nanorods have been the subject of much research, the pathways for
controlling their shape and thereby their optical properties remain largely heuristically …

Automatically identifying chemical and drug names in scientific publications advances
information access for this important class of entities in a variety of biomedical disciplines by …

Collecting and analyzing the vast amount of information available in the solid-state
chemistry literature may accelerate our understanding of materials synthesis. However, one …

In recent years, with the growing amount of biomedical documents, coupled with
advancement in natural language processing algorithms, the research on biomedical …

Motivation Language models pre-trained on biomedical corpora, such as BioBERT, have
recently shown promising results on downstream biomedical tasks. Many existing pre …

Background Biomedical named entity recognition (BioNER) is a basic and important medical
information extraction task to extract medical entities with special meaning from medical …

Extracting typed entity mentions from text is a fundamental component to language
understanding and reasoning. While there exist substantial labeled text datasets for multiple …