Year: 2025
Type: conference-paper
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 ERNIE 4-turbo .We release Chumor at https
Authors: Ruiqi He, Yushu He, Longju Bai, Jiarui Liu, Zhenjie Sun, Zenghao Tang, He Wang, Hanchen Xia, Rada Mihalcea, Naihao Deng
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4412887844