Personalize at Test Time: Learning User Preferences for Image Generation
arXiv:2610.09015v1 Announce Type: new Abstract: Diffusion models can generate high-quality images, yet aligning their outputs with individual user preferences remains challenging. A key bottleneck is accurately modeling diverse user preferences from limited feedback. Existing approaches often rely…
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- 2026-10-08 04:00 · arXiv cs.CV
Personalize at Test Time: Learning User Preferences for Image Generation