We propose Diffusion Adaptive Text Embedding (DATE), which improves text-to-image diffusion models by dynamically refining text embeddings throughout the diffusion sampling process.

We propose a training-free safe generation method to guide text embeddings for safe text-to-image diffusion models.

We propose BPO; a generalized DPO objective based on Bregman divergence from the perspective of likelihood ratio estimation.