Self-discovering interpretable diffusion latent directions for responsible text-to-image generation
Diffusion-based models have gained significant popularity for text-to-image generation due to their exceptional image-generation capabilities. A risk with these models is the potential generation of inappropriate content, such as biased or harmful images. However, the underlying reasons for generati...
| Main Authors: | , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
IEEE
2024
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