Emulating Author Style: A Feasibility Study of Prompt-enabled Text Stylization with Off-the-Shelf LLMs

[Published in the Personalization of Generative AI (PERSONALIZE) workshop (EACL2024) (https://aclanthology.org/2024.personalize-1.6/)]

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 prompt-enabled stylization in related fields, this work conducts the first feasibility study into 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.

If you use this repository in your research, please cite it using the following BibTeX entry:

@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",
}