# Combating the "Sameness" in AI Art: Reflections on the Interactive AI Installation Fencing Hallucination

arXiv: https://arxiv.org/abs/2311.17080 · HTML: https://mlsanity.com/paper/2311.17080/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 7 references that are in the map.
- First posted on arXiv 28 Nov 2023.

## Builds on (most cited first, 3 of 3)

- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms](https://mlsanity.com/paper/1706.07068/) (2017)

## Built on by (most cited first, 1 of 1)

- [Towards Kinetic Manipulation of the Latent Space](https://mlsanity.com/paper/2409.09867/) (2024)

## Abstract (arXiv)

The article summarizes three types of "sameness" issues in Artificial Intelligence(AI) art, each occurring at different stages of development in AI image creation tools. Through the Fencing Hallucination project, the article reflects on the design of AI art production in alleviating the sense of uniformity, maintaining the uniqueness of images from an AI image synthesizer, and enhancing the connection between the artworks and the audience. This paper endeavors to stimulate the creation of distinctive AI art by recounting the efforts and insights derived from the Fencing Hallucination project, all dedicated to addressing the issue of "sameness".