AI RESEARCH
HyperAlign: Hypernetwork for Efficient Test-Time Alignment of Diffusion Models
arXiv CS.CV
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ArXi:2601.15968v2 Announce Type: replace Diffusion model alignment aims to bridge the gap between generated outputs and human preferences by enhancing both semantic consistency with textual prompts and overall visual quality. Existing alignment methods face a challenging trade-off: test-time approaches enable input-specific adaptability but