@inproceedings{he-etal-2025-chumor,
    title = "Chumor 2.0: Towards Better Benchmarking {C}hinese Humor Understanding from (Ruo Zhi Ba)",
    author = "He, Ruiqi  and
      He, Yushu  and
      Bai, Longju  and
      Liu, Jiarui  and
      Sun, Zhenjie  and
      Tang, Zenghao  and
      Wang, He  and
      Xia, Hanchen  and
      Mihalcea, Rada  and
      Deng, Naihao",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingestion-acl-25/2025.findings-acl.1122/",
    pages = "21799--21818",
    ISBN = "979-8-89176-256-5",
    abstract = "Existing humor datasets and evaluations predominantly focus on English, leaving limited resources for culturally nuanced humor in non-English languages like Chinese. To address this gap, we construct **Chumor**, the first and the largest Chinese humor explanation dataset. **Chumor** is sourced from Ruo Zhi Ba (RZB, 弱智吧), a Chinese Reddit-like platform known for sharing intellectually challenging and culturally specific jokes. We test ten LLMs through direct and chain-of-thought prompting, revealing that **Chumor** poses significant challenges to existing LLMs, with their accuracy slightly above random and far below human. In addition, our analysis highlights that human-annotated humor explanations are significantly better than those generated by GPT-4o and ERNIE4-turbo. We release **Chumor** at https://huggingface.co/datasets/MichiganNLP/Chumor , our project page is at https://github.com/MichiganNLP/Chumor-2.0 , our leaderboard is at https://huggingface.co/spaces/MichiganNLP/Chumor-leaderboard , and our codebase is at https://github.com/MichiganNLP/Chumor-2.0 ."
}