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 …

Large Language Models (LLMs) have emerged as a transformative power in enhancing
natural language comprehension, representing a significant stride toward artificial general …

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 …

The development of open-source, multilingual medical language models can benefit a wide,
linguistically diverse audience from different regions. To promote this domain, we present …

Large language models (LLMs) have emerged as powerful tools in chemistry, significantly
impacting molecule design, property prediction, and synthesis optimization. This review …

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 …

Generalist Large Language Models (LLMs), such as GPT-4, have shown considerable
promise in various domains, including medical diagnosis. Rare diseases, affecting …

Retrieval-augmented generation (RAG) involves a solution by retrieving knowledge from an
established database to enhance the performance of large language models (LLM)., these …

In this study, we present MedS-Bench, a comprehensive benchmark to evaluate large
language models (LLMs) in clinical contexts, MedS-Bench, spanning 11 high-level clinical …

Recent advancements in large language models (LLMs) have achieved promising
performances across various applications. Nonetheless, the ongoing challenge of …