ChatGPT has drawn considerable attention from both the general public and domain experts
with its remarkable text generation capabilities. This has subsequently led to the emergence …

Pre-trained Language Models (PLMs) which are trained on large text corpus via self-
supervised learning method, have yielded promising performance on various tasks in …

Information overload is a major obstacle to scientific progress. The explosive growth in
scientific literature and data has made it ever harder to discover useful insights in a large …

Pretraining large neural language models, such as BERT, has led to impressive gains on
many natural language processing (NLP) tasks. However, most pretraining efforts focus on …

Motivation Biomedical text mining is becoming increasingly important as the number of
biomedical documents rapidly grows. With the progress in natural language processing …

Purpose To investigate if tailoring a transformer-based language model to radiology is
beneficial for radiology natural language processing (NLP) applications. Materials and …

Despite recent advances in natural language processing, many statistical models for
processing text perform extremely poorly under domain shift. Processing biomedical and …

Natural language processing (NLP) is useful for handling text and speech, and sequence
labeling plays an important role by automatically analyzing a sequence (text) to assign …

Pre-trained language models (PLMs) have been the de facto paradigm for most natural
language processing tasks. This also benefits the biomedical domain: researchers from …

A large array of pretrained models are available to the biomedical NLP (BioNLP) community.
Finding the best model for a particular task can be difficult and time-consuming. For many …