3 citations · 6 across the 6 of their papers we have counts for
6 papers · 1 filter
Pre-Trained Language Models Represent Some Geographic Populations Better Than Others
Jonathan Dunn, Benjamin Adams, Harish Tayyar Madabushi
This paper measures the skew in how well two families of LLMs represent diverse geographic populations. A spatial probing task is used with geo-referenced corpora to measure the de…
Geographically-Informed Language Identification
Jonathan Dunn, Lane Edwards-Brown
This paper develops an approach to language identification in which the set of languages considered by the model depends on the geographic origin of the text in question. Given tha…
Syntactic Variation Across the Grammar: Modelling a Complex Adaptive System
Jonathan Dunn
While language is a complex adaptive system, most work on syntactic variation observes a few individual constructions in isolation from the rest of the grammar. This means that the…
cantnlp@LT-EDI-2023: Homophobia/Transphobia Detection in Social Media Comments using Spatio-Temporally Retrained Language Models
Sidney G. -J. Wong, Matthew Durward, Benjamin Adams +1
This paper describes our multiclass classification system developed as part of the LTEDI@RANLP-2023 shared task. We used a BERT-based language model to detect homophobic and transp…
Variation and Instability in Dialect-Based Embedding Spaces
Jonathan Dunn
This paper measures variation in embedding spaces which have been trained on different regional varieties of English while controlling for instability in the embeddings. While prev…
Exploring the Constructicon: Linguistic Analysis of a Computational CxG
Jonathan Dunn
Recent work has formulated the task for computational construction grammar as producing a constructicon given a corpus of usage. Previous work has evaluated these unsupervised gram…