In a recent paper, Aceves and Evans computed information and semantic density measures
for hundreds of languages, and showed that these measures predict the pace and breadth …

Word embedding models are a powerful approach for representing the multidimensional
conceptual spaces within which communicated concepts relate, combine, and compete with …

This study empirically investigates claims of the increasing ubiquity of artificial intelligence
(AI) within roughly 80 million research publications across 20 diverse scientific fields, by …

Static word embeddings are ubiquitous in computational social science applications and
contribute to practical decision-making in a variety of fields including law and healthcare …

The doctor–patient relationship has received widespread attention as a significant global
issue affecting people's livelihoods. In clinical practice within the medical field, applying …

How does meaning vary across the world's languages? Scholars recognize the existence of
substantial variability within specific domains, ranging from nature and color to kinship. The …

In a response to Aceves and Evans 1, Koplenig 2 argues that once the influence of corpus
size (by which he means the length of the document in number of words) is accounted for …

In a previous study, Aceves and Evans present a large-scale quantitative information-
theoretic analysis of parallel corpus data in~ 1,000 languages to show that there are …