Efficient Diffusion Personalization

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Most implemented papers archive 2025-07-28

4 shown of 4 papers with code (5 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual Prompting
  26 Jan 2025 1 repository listed
  The stories and characters that captivate us as we grow up shape unique fantasy worlds, with images serving as the primary medium for visually experiencing these realms.
• DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning
  13 Apr 2023 1 repository listed
  This paper proposes DiffFit, a parameter-efficient strategy to fine-tune large pre-trained diffusion models that enable fast adaptation to new domains.
• A Closer Look at Parameter-Efficient Tuning in Diffusion Models
  31 Mar 2023 1 repository listed Syntology ran 13 of 14 samples · 1 unverified
  Large-scale diffusion models like Stable Diffusion are powerful and find various real-world applications while customizing such models by fine-tuning is both memory and time inefficient.
• SVDiff: Compact Parameter Space for Diffusion Fine-Tuning
  20 Mar 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Diffusion models have achieved remarkable success in text-to-image generation, enabling the creation of high-quality images from text prompts or other modalities.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.