@inproceedings{abbas-abdul-rauf-2026-slpgfjwuinsa,
    title = "{SLPGFJWUI}nsa at {S}em{E}val-2026 Task 1: Enhancing Linguistic Creativity for {E}nglish Text-Based Humor",
    author = "Abbas, Insa  and
      Abdul Rauf, Sadaf",
    editor = "Kochmar, Ekaterina  and
      Ghosh, Debanjan  and
      North, Kai  and
      Komachi, Mamoru",
    booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.semeval-1.231/",
    pages = "1832--1839",
    ISBN = "979-8-89176-414-9",
    abstract = "For Subtask A, our main goal is to create a joke generating system that focuses on humor generation under constrained conditions using unusual words and news headlines as input. We trained our model on LLM-generated and human-curated augmented data aimed to produce constrained humor and to bridge the gap between the two. We demonstrate that using parameter-efficient fine-tuning (PEFT) on high-quality pre-trained base models in conjunction with a well-crafted prompt design allows our model to produce high-quality innovative output while maintaining the desired style."
}