The deployment of large language models (LLMs) within the healthcare sector has sparked
both enthusiasm and apprehension. These models exhibit the remarkable ability to provide …

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 …

The utilization of large language models (LLMs) for Healthcare has generated both
excitement and concern due to their ability to effectively respond to free-text queries with …

Traditional biomedical artificial intelligence (AI) models, designed for specific tasks or
modalities, often exhibit limited flexibility in real-world deployment and struggle to utilize …

Abstract Recently, Large Language Models (LLMs) have demonstrated impressive
capability to solve a wide range of tasks. However, despite their success across various …

Foundation model, trained on a diverse range of data and adaptable to a myriad of tasks, is
advancing healthcare. It fosters the development of healthcare artificial intelligence (AI) …

In the past few years, large pre-trained language models (PLMs) have been widely adopted
in different areas and have made fundamental improvements over a variety of downstream …

This paper presents the setup and results of the second edition of the BioLaySumm shared
task on the Lay Summarisation of Biomedical Research Articles, hosted at the BioNLP …

The integration of biomolecular modeling with natural language (BL) has emerged as a
promising interdisciplinary area at the intersection of artificial intelligence, chemistry and …

Since the inception of the Transformer architecture in 2017, Large Language Models (LLMs)
such as GPT and BERT have evolved significantly, impacting various industries with their …