20 citations · 72 across the 17 of their papers we have counts for
6 papers · 1 filter
Tokens, the oft-overlooked appetizer: Large language models, the distributional hypothesis, and meaning
Julia Witte Zimmerman, Denis Hudon, Kathryn Cramer +9
Tokenization is a necessary component within the current architecture of many language mod-els, including the transformer-based large language models (LLMs) of Generative AI, yet i…
A blind spot for large language models: Supradiegetic linguistic information
Julia Witte Zimmerman, Denis Hudon, Kathryn Cramer +5
Large Language Models (LLMs) like ChatGPT reflect profound changes in the field of Artificial Intelligence, achieving a linguistic fluency that is impressively, even shockingly, hu…
A decomposition of book structure through ousiometric fluctuations in cumulative word-time
Mikaela Irene Fudolig, Thayer Alshaabi, Kathryn Cramer +2
While quantitative methods have been used to examine changes in word usage in books, studies have focused on overall trends, such as the shapes of narratives, which are independent…
Augmenting semantic lexicons using word embeddings and transfer learning
Thayer Alshaabi, Colin M. Van Oort, Mikaela Irene Fudolig +3
Sentiment-aware intelligent systems are essential to a wide array of applications. These systems are driven by language models which broadly fall into two paradigms: Lexicon-based…
Ousiometrics: The essence of meaning aligns with a power-danger-structure framework instead of valence-arousal-dominance
P. S. Dodds, T. Alshaabi, M. I. Fudolig +7
From work emerging through the middle of the 20th century, the essence of meaning has become widely accepted as being described by the three orthogonal dimensions of valence, arous…
Sentiment and structure in word co-occurrence networks on Twitter
Mikaela Irene Fudolig, Thayer Alshaabi, Michael V. Arnold +2
We explore the relationship between context and happiness scores in political tweets using word co-occurrence networks, where nodes in the network are the words, and the weight of…