Defining and Quantifying Creative Behavior in Popular Image Generators

Fuente: arXiv
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Autori principali: Ramaswamy, Aditi, Chockler, Hana, Navaratnarajah, Melane
Natura: Preprint
Pubblicazione: 2025
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author Ramaswamy, Aditi
Chockler, Hana
Navaratnarajah, Melane
author_facet Ramaswamy, Aditi
Chockler, Hana
Navaratnarajah, Melane
contents Creativity of generative AI models has been a subject of scientific debate in the last years, without a conclusive answer. In this paper, we study creativity from a practical perspective and introduce quantitative measures that help the user to choose a suitable AI model for a given task. We evaluated our measures on a number of popular image-to-image generation models, and the results of this suggest that our measures conform to human intuition.
format Preprint
id arxiv_https___arxiv_org_abs_2505_04497
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Defining and Quantifying Creative Behavior in Popular Image Generators
Ramaswamy, Aditi
Chockler, Hana
Navaratnarajah, Melane
Computer Vision and Pattern Recognition
Artificial Intelligence
I.4.m; I.2.m
Creativity of generative AI models has been a subject of scientific debate in the last years, without a conclusive answer. In this paper, we study creativity from a practical perspective and introduce quantitative measures that help the user to choose a suitable AI model for a given task. We evaluated our measures on a number of popular image-to-image generation models, and the results of this suggest that our measures conform to human intuition.
title Defining and Quantifying Creative Behavior in Popular Image Generators
topic Computer Vision and Pattern Recognition
Artificial Intelligence
I.4.m; I.2.m
url https://arxiv.org/abs/2505.04497