Is AI fun? HumorDB: a curated dataset and benchmark to investigate graphical humor

• URL: http://arxiv.org/abs/2406.13564v1
• Date: Wed, 19 Jun 2024 13:51:40 GMT
• Title: Is AI fun? HumorDB: a curated dataset and benchmark to investigate graphical humor
• Authors: Veedant Jain, Felipe dos Santos Alves Feitosa, Gabriel Kreiman,
• Abstract summary: HumorDB is an image-only dataset specifically designed to advance visual humor understanding. The dataset enables evaluation through binary classification, range regression, and pairwise comparison tasks. HumorDB shows potential as a valuable benchmark for powerful large multimodal models.
• Score: 8.75275650545552
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Despite significant advancements in computer vision, understanding complex scenes, particularly those involving humor, remains a substantial challenge. This paper introduces HumorDB, a novel image-only dataset specifically designed to advance visual humor understanding. HumorDB consists of meticulously curated image pairs with contrasting humor ratings, emphasizing subtle visual cues that trigger humor and mitigating potential biases. The dataset enables evaluation through binary classification(Funny or Not Funny), range regression(funniness on a scale from 1 to 10), and pairwise comparison tasks(Which Image is Funnier?), effectively capturing the subjective nature of humor perception. Initial experiments reveal that while vision-only models struggle, vision-language models, particularly those leveraging large language models, show promising results. HumorDB also shows potential as a valuable zero-shot benchmark for powerful large multimodal models. We open-source both the dataset and code under the CC BY 4.0 license.

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