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Found 2 papers, 1 papers with code
Directly Fine-Tuning Diffusion Models on Differentiable Rewards
We present Direct Reward Fine-Tuning (DRaFT), a simple and effective method for fine-tuning diffusion models to maximize differentiable reward functions, such as scores from human preference models.
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding.
Ranked #17 on
Text-to-Image Generation
on MS COCO
(using extra training data)
