Gan, Q.; Dunn, J.; Nini, A.; & Adams, B. (2026). “A Multi-Dialectal, Longitudinal Corpus of Human-AI Hybrid Language Production.” In Proceedings of the International Conference on Language Resources and Evaluation. ERLA. Abstract. This paper describes a multi-dialectal, longitudinal corpus of human-AI hybrid language production, which includes purely human-produced samples, purely LLM-generated samples, and hybrid samples … More A Multi-Dialectal, Longitudinal Corpus of Human-AI Hybrid Language Production

Dunn, J. (2025). “Diffusion Across the Grammar: Complexity in Areal Interactions Between Dialects of English.” In Enrique-Arias, Andrés, Carlota de Benito Moreno and Florencio del Barrio de la Rosa (eds.). The spatial diffusion of linguistic changes: new methods and theoretical perspectives. Berlin: De Gruyter. Studies in Language Change 26. Abstract. This paper experiments with the … More Diffusion Across the Grammar: Complexity in Areal Interactions Between Dialects of English

Dunn, J.; Adams, B.; and Tayyar Madabushi, H. (2023). “Pre-Trained Language Models Represent Some Geographic Populations Better Than Others.” In Proceedings of the Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC/COLING 2024). 12966–12976 Abstract. This paper measures the skew in how well two families of LLMs represent diverse geographic populations. A spatial … More Pre-Trained Language Models Represent Some Geographic Populations Better Than Others

Dunn, J. (2023). “Syntactic variation across the grammar: modelling a complex adaptive system.” Frontiers in Complex Systems. DOI: 10.3389/fcpxs.2023.1273741 Abstract. 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 grammar, a network which connects thousands … More Syntactic Variation Across the Grammar: Modelling a complex adaptive system

Dunn, J. (2023). “Variation and Instability in Dialect-Based Embedding Spaces.” In Proceedings of the Workshop on NLP for Similar Languages, Varieties and Dialects. Association for Computational Linguistics. Abstract. 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 previous work … More Variation and Instability in Dialect-Based Embedding Spaces

Dunn, J. and Wong, S. (2022). “Stability of Syntactic Dialect Classification Over Space and Time.” In Proceedings of International Conference on Computational Linguistics (COLING 2022). 26-36. Abstract. This paper analyses the degree to which dialect classifiers based on syntactic representations remain stable over space and time. While previous work has shown that the combination of … More Stability of Syntactic Dialect Classification Over Space and Time