TY - CONF A1 - Römisch, Johannes A1 - Gorovaia, Svetlana A1 - Halchynska, Mariia A1 - Schmidt, Gleb A1 - Yamshchikov, Ivan P. T1 - Better Call Claude: Can LLMs Detect Changes of Writing Style? T2 - Lecture Notes in Computer Science N2 - This article explores the zero-shot performance of state-ofthe-art large language models (LLMs) on one of the most challenging tasks in authorship analysis: sentence-level style change detection. Benchmarking four LLMs on the official PAN 2024 and 2025 “MultiAuthor Writing Style Analysis” datasets, we present several observations. First, state-of-the-art generative models are sensitive to variations in writing style—even at the granular level of individual sentences. Second, their accuracy establishes a challenging baseline for the task, outperforming suggested baselines of the PAN competition. Finally, we explore the influence of semantics on model predictions and present evidence suggesting that the latest generation of LLMs may be more sensitive to content-independent and purely stylistic signals than previously reported. KW - LLM KW - Style Detection Y1 - 2025 UR - https://opus4.kobv.de/opus4-fhws/frontdoor/index/index/docId/6282 UR - https://nbn-resolving.org/urn:nbn:de:bvb:863-opus-62822 SN - 9783032043535 SN - 0302-9743 SP - 42 EP - 56 PB - Springer Nature Switzerland CY - Cham ER -