Date of Award
Spring 6-4-2025
Document Type
Thesis (Undergraduate)
Department
Computer Science
First Advisor
Dan Rockmore
Abstract
We present a novel stylometric approach using large language models. By training separate models on individual authors' works, we find that each model achieves lower cross-entropy loss when predicting text from its training author compared to other authors' texts. Moreover, for any given text, the model trained on its true author’s corpus yields the lowest loss. We suggest that, in this way, a model trained on one author's works embodies the unique writing style of that author. We demonstrate our approach on works by eight known authors. This approach also confirms that R. P. Thompson wrote the well-studied 15th book of the Oz series, originally attributed to F. L. Baum.
Recommended Citation
Stropkay, Harrison F., "An Approach to Stylometry using Causal Language Models" (2025). Computer Science Senior Theses. 91.
https://digitalcommons.dartmouth.edu/cs_senior_theses/91
