Text-to-image models suffer from various safety issues that may limit their suitability for
deployment. Previous methods have separately addressed individual issues of bias …

Recently, the text-to-image diffusion model has gained considerable attention from the
community due to its exceptional image generation capability. A representative model …

The rapid expansion of large-scale text-to-image diffusion models has raised growing
concerns regarding their potential misuse in creating harmful or misleading content. In this …

While text-to-image diffusion models demonstrate impressive generation capabilities, they
also exhibit vulnerability to backdoor attacks, which involve the manipulation of model …

Text-to-image diffusion models (T2I) use a latent representation of a text prompt to guide the
image generation process. However, the process by which the encoder produces the text …

Text-to-image (T2I) diffusion models enjoy great popularity and many individuals and
companies build their applications based on publicly released T2I diffusion models …

During pre-training, the Text-to-Image (T2I) diffusion models encode factual knowledge into
their parameters. These parameterized facts enable realistic image generation, but they may …

Text-to-image diffusion models suffer from the risk of generating outdated, copyrighted,
incorrect, and biased content. While previous methods have mitigated the issues on a small …

Recent advancements in NLP systems, particularly with the introduction of LLMs, have led to
widespread adoption of these systems by a broad spectrum of users across various …