@inproceedings{baluja-2025-text,
title = "Text Is Not All You Need: Multimodal Prompting Helps {LLM}s Understand Humor",
author = "Baluja, Ashwin",
editor = "Hempelmann, Christian F. and
Rayz, Julia and
Dong, Tiansi and
Miller, Tristan",
booktitle = "Proceedings of the 1st Workshop on Computational Humor (CHum)",
month = jan,
year = "2025",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.chum-1.2/",
pages = "9--17",
abstract = "While Large Language Models (LLMs) have demonstrated impressive natural language understanding capabilities across various text-based tasks, understanding humor has remained a persistent challenge. Humor is frequently multimodal, relying not only on the meaning of the words, but also their pronunciations, and even the speaker`s intonations. In this study, we explore a simple multimodal prompting approach to humor understanding and explanation. We present an LLM with both the text and the spoken form of a joke, generated using an off-the-shelf text-to-speech (TTS) system. Using multimodal cues improves the explanations of humor compared to textual prompts across all tested datasets."
}
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%0 Conference Proceedings
%T Text Is Not All You Need: Multimodal Prompting Helps LLMs Understand Humor
%A Baluja, Ashwin
%Y Hempelmann, Christian F.
%Y Rayz, Julia
%Y Dong, Tiansi
%Y Miller, Tristan
%S Proceedings of the 1st Workshop on Computational Humor (CHum)
%D 2025
%8 January
%I Association for Computational Linguistics
%C Online
%F baluja-2025-text
%X While Large Language Models (LLMs) have demonstrated impressive natural language understanding capabilities across various text-based tasks, understanding humor has remained a persistent challenge. Humor is frequently multimodal, relying not only on the meaning of the words, but also their pronunciations, and even the speaker‘s intonations. In this study, we explore a simple multimodal prompting approach to humor understanding and explanation. We present an LLM with both the text and the spoken form of a joke, generated using an off-the-shelf text-to-speech (TTS) system. Using multimodal cues improves the explanations of humor compared to textual prompts across all tested datasets.
%U https://aclanthology.org/2025.chum-1.2/
%P 9-17
Markdown (Informal)
[Text Is Not All You Need: Multimodal Prompting Helps LLMs Understand Humor](https://aclanthology.org/2025.chum-1.2/) (Baluja, chum 2025)
ACL