AI RESEARCH
D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models
arXiv CS.CV
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ArXi:2605.05204v1 Announce Type: new The landscape of high-performance image generation models is currently shifting from the inefficient multi-step ones to the efficient few-step counterparts (e.g, Z-Image-Turbo and FLUX.2-klein). However, these models present significant challenges for directly continuous supervised fine-tuning. For example, applying the commonly used fine-tuning technique would compromises their inherent few-step inference capability. To address this, we propose D-OPSD, a novel