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.