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Gore Diffusion LoRA Model

arXiv 2403.08812 ↗First posted 9 Feb 2024cs.HC cs.GR cs.LGcited by 0

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Abstract (arXiv)

The Emergence of Artificial Intelligence (AI) has significantly impacted our engagement with violence, sparking ethical deliberations regarding the algorithmic creation of violent imagery. This paper scrutinizes the "Gore Diffusion LoRA Model," an innovative AI model proficient in generating hyper-realistic visuals portraying intense violence and bloodshed. Our exploration encompasses the model's technical intricacies, plausible applications, and the ethical quandaries inherent in its utilization. We contend that the creation and implementation of such models warrant a meticulous discourse concerning the convergence of AI, art, and violence. Furthermore, we advocate for a structured framework advocating responsible development and ethical deployment of these potent technologies.

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References · 8

  1. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  2. 2023Extracting Training Data from Diffusion Modelscited by 723
  3. 2023Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondencecited by 211
  4. 2020U-Net and its variants for medical image segmentation: theory and applicationscited by 169
  5. 2023Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRAcited by 138
  6. 2023DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Modelscited by 121
  7. 2023A Closer Look at Parameter-Efficient Tuning in Diffusion Modelscited by 15
  8. 2023Text-to-image Editing by Image Information Removalcited by 12

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