Defining and Quantifying Creative Behavior in Popular Image Generators
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866916725845393408 |
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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 |