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Feedback Efficient Online Fine-Tuning of Diffusion Models
Feb. 27, 2024, 5:42 a.m. | Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M Tseng, Sergey Levine, Tommaso Biancala
cs.LG updates on arXiv.org arxiv.org
Abstract: Diffusion models excel at modeling complex data distributions, including those of images, proteins, and small molecules. However, in many cases, our goal is to model parts of the distribution that maximize certain properties: for example, we may want to generate images with high aesthetic quality, or molecules with high bioactivity. It is natural to frame this as a reinforcement learning (RL) problem, in which the objective is to fine-tune a diffusion model to maximize a …
abstract arxiv cases cs.ai cs.lg data diffusion diffusion models distribution example excel feedback fine-tuning generate images modeling molecules proteins q-bio.qm quality small stat.ml type
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