@inproceedings{arora-hoblitzell-2026-bahaha,
    title = "{BAHAHA} at {S}em{E}val-2026 Task 1: Benchmarking-Aware Humor Authoring with Hybrid Assessment and Adaptation",
    author = "Arora, Utsav  and
      Hoblitzell, Andrew",
    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-1.110/",
    pages = "785--792",
    ISBN = "979-8-89176-414-9",
    abstract = "This paper describes the BAHAHA system for SemEval-2026 Task 1: MWAHAHA, which requires generating original jokes given either a news headline or a pair of rare words. Our approach uses a generate-then-rank pipeline, combining multi-style candidate generation via comedian-inspired few-shot prompting. We perform quality assessment from a smaller model fine-tuned on synthetic rating data from the generation model. Specifically, we produce up to 50 candidates per input across 15 stylistic templates and select outputs through a mixed-initiative interface that combines automated ranking with human judgment. There were 305 participants and 180 submissions in the contest. Our system ranks 2nd on Subtask A Chinese and 5th on Subtasks B1 and B2. The system generates jokes natively in each language rather than through translation."
}