Large language models (LLMs), such as ChatGPT, have received substantial attention due
to their capabilities for understanding and generating human language. While there has …

Applying artificial intelligence (AI), especially natural language processing (NLP), to harness
large amounts of information from patent databases, online communities, social media, or …

A long-running goal of the clinical NLP community is the extraction of important variables
trapped in clinical notes. However, roadblocks have included dataset shift from the general …

Machine learning currently exerts an outsized influence on the world, increasingly affecting
institutional practices and impacted communities. It is therefore critical that we question …

In this paper, the problem of wireless resource allocation and semantic information
extraction for energy efficient semantic communications over wireless networks with rate …

In this paper, a semantic communication framework is proposed for textual data
transmission. In the studied model, a base station (BS) extracts the semantic information …

Representation learning is a critical ingredient for natural language processing systems.
Recent Transformer language models like BERT learn powerful textual representations, but …

The volume of scientific output is creating an urgent need for automated tools to help
scientists keep up with developments in their field. Semantic Scholar (S2) is an open data …

Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging
and expensive. We release SciBERT, a pretrained language model based on BERT (Devlin …

A large amount of materials science knowledge is generated and stored as text published in
peer-reviewed scientific literature. While recent developments in natural language …