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Align-Prop
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We propose AlignProp, a method that uses reward backpropogation for the alignment of large-scale text-to-image diffusion models.
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2026-01-25 04:25:29
raw text
Align-Prop Aligning Text-to-Image Diffusion Models with Reward Backpropagation Mihir Prabhudesai 1 , Anirudh Goyal 2 , Deepak Pathak 1 , Katerina Fragkiadaki 1 1 Carnegie Mellon University, 2 Google DeepMind Paper Code Your browser does not support the video tag. AlignProp is a direct backpropagation-based approach to finetune text-to-image diffusion models for desired reward function. Above we show finetuning results for various reward functions. Abstract Text-to-image diffusion models have recently emerged at the forefront of image generation, powered by very large-scale unsupervised or weakly supervised text-to-image training datasets. Due to the unsupervised training, controlling their behavior in downstream tasks, such as maximizing human-perceived image quality, image-text alignment, or ethical image generation, is difficult. Recent works finetune diffusion models to downstream reward functions using vanilla reinf...
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