@inproceedings{bhandarkar-etal-2024-emulating,
title = "Emulating Author Style: A Feasibility Study of Prompt-enabled Text Stylization with Off-the-Shelf {LLM}s",
author = "Bhandarkar, Avanti and
Wilson, Ronald and
Swarup, Anushka and
Woodard, Damon",
editor = "Deshpande, Ameet and
Hwang, EunJeong and
Murahari, Vishvak and
Park, Joon Sung and
Yang, Diyi and
Sabharwal, Ashish and
Narasimhan, Karthik and
Kalyan, Ashwin",
booktitle = "Proceedings of the 1st Workshop on Personalization of Generative AI Systems (PERSONALIZE 2024)",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.personalize-1.6",
pages = "76--82",
abstract = "User-centric personalization of text opens many avenues of applications from stylized email composition to machine translation. Existing approaches in this domain often encounter limitations in data and resource requirements. Drawing inspiration from the success of resource-efficient prompt-enabled stylization in related fields, this work conducts the first feasibility into testing 12 pre-trained SOTA LLMs for author style emulation. Although promising, the results suggest that current off-the-shelf LLMs fall short of achieving effective author style emulation. This work provides valuable insights through which off-the-shelf LLMs could be potentially utilized for user-centric personalization easily and at scale.",
}
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%0 Conference Proceedings
%T Emulating Author Style: A Feasibility Study of Prompt-enabled Text Stylization with Off-the-Shelf LLMs
%A Bhandarkar, Avanti
%A Wilson, Ronald
%A Swarup, Anushka
%A Woodard, Damon
%Y Deshpande, Ameet
%Y Hwang, EunJeong
%Y Murahari, Vishvak
%Y Park, Joon Sung
%Y Yang, Diyi
%Y Sabharwal, Ashish
%Y Narasimhan, Karthik
%Y Kalyan, Ashwin
%S Proceedings of the 1st Workshop on Personalization of Generative AI Systems (PERSONALIZE 2024)
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julians, Malta
%F bhandarkar-etal-2024-emulating
%X User-centric personalization of text opens many avenues of applications from stylized email composition to machine translation. Existing approaches in this domain often encounter limitations in data and resource requirements. Drawing inspiration from the success of resource-efficient prompt-enabled stylization in related fields, this work conducts the first feasibility into testing 12 pre-trained SOTA LLMs for author style emulation. Although promising, the results suggest that current off-the-shelf LLMs fall short of achieving effective author style emulation. This work provides valuable insights through which off-the-shelf LLMs could be potentially utilized for user-centric personalization easily and at scale.
%U https://aclanthology.org/2024.personalize-1.6
%P 76-82
Markdown (Informal)
[Emulating Author Style: A Feasibility Study of Prompt-enabled Text Stylization with Off-the-Shelf LLMs](https://aclanthology.org/2024.personalize-1.6) (Bhandarkar et al., PERSONALIZE-WS 2024)
ACL