AI RESEARCH
Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning
arXiv CS.AI
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ArXi:2605.25210v1 Announce Type: cross Diffusion models are increasingly used as powerful conditional generators, yet real deployments often involve multiple target distributions arising from different tasks, e.g., diverse prompt domains in text-to-image generation, or multiple environments in robotics with diffusion policies. This naturally leads to a multi-objective learning (MOL) problem.