Sui Generis: Large Language Models for Authorship Attribution and Verification in Latin

• URL: http://arxiv.org/abs/2410.09245v1
• Date: Fri, 11 Oct 2024 20:41:49 GMT
• Title: Sui Generis: Large Language Models for Authorship Attribution and Verification in Latin
• Authors: Gleb Schmidt, Svetlana Gorovaia, Ivan P. Yamshchikov,
• Abstract summary: The study showcases that LLMs can be robust in zero-shot authorship verification even on short texts. The experiments also demonstrate that steering the model's authorship analysis and decision-making is challenging.
• Score: 6.704529554100875
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper evaluates the performance of Large Language Models (LLMs) in authorship attribution and authorship verification tasks for Latin texts of the Patristic Era. The study showcases that LLMs can be robust in zero-shot authorship verification even on short texts without sophisticated feature engineering. Yet, the models can also be easily "mislead" by semantics. The experiments also demonstrate that steering the model's authorship analysis and decision-making is challenging, unlike what is reported in the studies dealing with high-resource modern languages. Although LLMs prove to be able to beat, under certain circumstances, the traditional baselines, obtaining a nuanced and truly explainable decision requires at best a lot of experimentation.

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