Multi-Objective Prompt Optimization for Affective Text Generation

This page contains the supplementary material for the paper:

Yarik Menchaca Resendiz and Roman Klinger. Mopo: Multi-objective prompt optimization for affective text generation. In Proceedings of the 31st International Conference on Computational Linguistics, Abu Dhabi, UAE, October 2025. International Committee on Computational Linguistics. 

You can use the following Bib entry for citations:

 

@inproceedings{menchaca-resendiz-klinger-2025-mopo,
    title = "{MOPO}: Multi-Objective Prompt Optimization for Affective Text Generation",
    author = "Menchaca Resendiz, Yarik  and
      Klinger, Roman",
    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.375/",
    pages = "5588--5606"
}

 

You can find the code of our experiments at https://github.com/YarikMR/MOPO

In the case of questions, please write to yarik.menchaca-resendiz(at)uni-bamberg.de or roman.klinger(at)uni-bamberg.de.