Historical context & research account
SDXL develops composition, detail, style and resolution while retaining a model ecosystem that can be fine-tuned and combined with other tools. The master positions it within the Stable Diffusion community's movement from rapid experimentation toward more established production practices.
Dates & version record
Date displayed for this node：2023-07-26 · Date recorded in the research master：2023-07-26
These dates refer to the historical event or recorded version, not this page’s publication date. The original date precision and unresolved questions are retained.
Original sources & further reading
These links lead to the cited paper, article, institution or conference page. External texts retain their source languages.
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
https://stability.ai/news-updates/stable-diffusion-sdxl-1-announcement
Current cited URL
Provenance, translation & verification
Archive node #101 · Historical node
Research masters & supplement references · 3
AI Art Genealogy Research Master · p. 30 · 101
Date as recorded: 2023-07-26
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis ↗
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
GenAI Visual Release Chronology Research Master · p. 15 · R071
Date as recorded: 2023-07-26
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis ↗
SDXL 1.0
GenAI Visual Release Chronology Research Master · p. 15 · R072
Date as recorded: 2023-07-26
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis ↗
Stable Diffusion XL 1.0
Archive account adapted from the masters, not a full translation of the linked work. AI-assisted translation; human review pending.
The master’s research claims and dates await independent verification.
Cite this node
ANTI-AI ARCHIVE. SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis. Art-history node #101. https://salondesrefuses.cn/en/art-history/101
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