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Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search
2024-01-16
· ICLR 2024 poster ·
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Findings
IC-1012
Connected regions in the latent space of Stable Diffusion v2.1, v1.5, and GLIDE produce distorted images independent of the text prompt
IC-1013
Latent samples in Stable Diffusion v2.1, v1.5, and GLIDE can produce images of associated backgrounds rather than the key object, with failure rates of 2.7%, 9.2%, and 50.5% under random sampling respectively
IC-1014
A single adversarial token embedding appended to any input prompt overwrites the prompt in Stable Diffusion v2.1 to generate a target object, with CLIP similarity to the original prompt (0.742) remaining higher than to the target (0.546)