@inproceedings{icard-etal-2025-embedding,
title = "Embedding Style Beyond Topics: Analyzing Dispersion Effects Across Different Language Models",
author = "Icard, Benjamin and
Zve, Evangelia and
Sainero, Lila and
Breton, Alice and
Ganascia, Jean-Gabriel",
editor = "Rambow, Owen and
Wanner, Leo and
Apidianaki, Marianna and
Al-Khalifa, Hend and
Eugenio, Barbara Di and
Schockaert, Steven",
booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.coling-main.236/",
pages = "3511--3522",
abstract = "This paper analyzes how writing style affects the dispersion of embedding vectors across multiple, state-of-the-art language models. While early transformer models primarily aligned with topic modeling, this study examines the role of writing style in shaping embedding spaces. Using a literary corpus that alternates between topics and styles, we compare the sensitivity of language models across French and English. By analyzing the particular impact of style on embedding dispersion, we aim to better understand how language models process stylistic information, contributing to their overall interpretability."
}
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%0 Conference Proceedings
%T Embedding Style Beyond Topics: Analyzing Dispersion Effects Across Different Language Models
%A Icard, Benjamin
%A Zve, Evangelia
%A Sainero, Lila
%A Breton, Alice
%A Ganascia, Jean-Gabriel
%Y Rambow, Owen
%Y Wanner, Leo
%Y Apidianaki, Marianna
%Y Al-Khalifa, Hend
%Y Eugenio, Barbara Di
%Y Schockaert, Steven
%S Proceedings of the 31st International Conference on Computational Linguistics
%D 2025
%8 January
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F icard-etal-2025-embedding
%X This paper analyzes how writing style affects the dispersion of embedding vectors across multiple, state-of-the-art language models. While early transformer models primarily aligned with topic modeling, this study examines the role of writing style in shaping embedding spaces. Using a literary corpus that alternates between topics and styles, we compare the sensitivity of language models across French and English. By analyzing the particular impact of style on embedding dispersion, we aim to better understand how language models process stylistic information, contributing to their overall interpretability.
%U https://aclanthology.org/2025.coling-main.236/
%P 3511-3522
Markdown (Informal)
[Embedding Style Beyond Topics: Analyzing Dispersion Effects Across Different Language Models](https://aclanthology.org/2025.coling-main.236/) (Icard et al., COLING 2025)
ACL