AAAI 2026technical0 citations
Assessing the Capabilities of LLMs in Humor: A Multi-dimensional Analysis of Oogiri Generation and Evaluation
Ritsu Sakabe, Hwichan Kim, Tosho Hirasawa, Mamoru Komachi
Abstract
Computational humor is a frontier for creating advanced and engaging natural language processing (NLP) applications, such as sophisticated dialogue systems. While previous studies have benchmarked the humor capabilities of Large Language Models (LLMs), they have often relied on single-dimensional evaluations, such as judging whether something is simply ``funny.
BibTeX
@inproceedings{aaai2026_assessingthecapa,
title = {Assessing the Capabilities of LLMs in Humor: A Multi-dimensional Analysis of Oogiri Generation and Evaluation},
author = {Ritsu Sakabe and Hwichan Kim and Tosho Hirasawa and Mamoru Komachi},
booktitle = {AAAI 2026},
year = {2026}
}