Recently, research on short text topic models has addressed the challenges of social media
datasets. These models are typically evaluated using automated measures. However, recent …

Abstract Language models (LMs) like GPT‐3, PaLM, and ChatGPT are the foundation for
almost all major language technologies, but their capabilities, limitations, and risks are not …

Advances in technology, including novel ophthalmic imaging devices and adoption of the
electronic health record (EHR), have resulted in significantly increased data available for …

Artificial intelligence (AI) systems have begun to be deployed in high-stakes contexts,
including autonomous driving and medical diagnosis. In contexts such as these, the …

Word co‐occurrence patterns in language corpora contain a surprising amount of
conceptual knowledge. Large language models (LLMs), trained to predict words in context …

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 …

Functionalist accounts of language suggest that forms are paired with meanings in ways that
support efficient communication. Previous work on grammatical marking suggests that word …

Background While representation learning techniques have shown great promise in
application to a number of different NLP tasks, they have had little impact on the problem of …

Objectives Biomedical natural language processing tools are increasingly being applied for
broad-coverage information extraction—extracting medical information of all types in a …

This paper presents an algorithm for learning the construction grammar of a language from a
large corpus. This grammar induction algorithm has two goals: first, to show that construction …