Large-language models (LLMs) such as GPT-4 caught the interest of many scientists.
Recent studies suggested that these models could be useful in chemistry and materials …

High-fidelity computer-aided experimentation is becoming more accessible with the
development of computing power and artificial intelligence tools. The advancement of …

A bottleneck in efficiently connecting new materials discoveries to established literature has
arisen due to an increase in publications. This problem may be addressed by using named …

Large language models (LLMs) hold great promise in summarizing medical evidence. Most
recent studies focus on the application of proprietary LLMs. Using proprietary LLMs …

In the electronic health record, using clinical notes to identify entities such as disorders and
their temporality (eg the order of an event relative to a time index) can inform many important …

Abstract Representations from artificial neural network (ANN) language models have been
shown to predict human brain activity in the language network. To understand what aspects …

Biomedical research yields vast information, much of which is only accessible through the
literature. Consequently, literature search is crucial for healthcare and biomedicine. Recent …

This paper proposes a new deep learning approach to better understand how optimistic and
pessimistic feelings are conveyed in Twitter conversations about COVID-19. A pre-trained …

Nanophotonic devices manipulate light at sub-wavelength scales, enabling tasks such as
light concentration, routing, and filtering. Designing these devices to achieve precise light …

Language models exhibit a profound aptitude for addressing multimodal and multidomain
challenges, a competency that eludes the majority of off-the-shelf machine learning models …