AI RESEARCH
Polaris: Scaling Up Instruction-Guided Image Generation Towards Millions of Personalized Style Needs
arXiv CS.CV
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ArXi:2606.01858v1 Announce Type: new Users increasingly expect image generation models to quickly adapt to highly diverse and personalized requirements, such as producing images with distinctive styles or characteristics. Traditional approaches rely on fine-tuning, which is costly and difficult to scale. To cope with these limitations, the community has accumulated a growing library of fine-tuned modules and adapters, where each component targets specific generation needs and collectively serves as a foundation for handling new demands. This naturally raises a question: instead of repeatedly.