Introduction
GLIDE compares CLIP guidance with classifier-free guidance and demonstrates photorealistic text-to-image generation and inpainting. It is a precursor to DALL·E 2 and later diffusion-based products. The combination of generation and editing is especially relevant to the development of interfaces for modifying existing visual material.
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Alex Nichol; Prafulla Dhariwal et al. / OpenAI · original paper · Image rights remain with their respective holders; no open licence is asserted
Source · GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗RESEARCH ACCOUNT
Connecting text guidance with local image editing.
ANTI-AI ARCHIVE · Revised 2026-10-02
Method and contribution
GLIDE compares CLIP guidance with classifier-free guidance, reporting a preference for the latter in its human evaluations. Fine-tuning also enables inpainting, connecting language with local edits. The smaller released model was trained on filtered data and should not be conflated with every system evaluated in the research.
Section sources: GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Art-historical interpretation
Generation and revision become stages in a continuous process: a picture can serve as input to its next transformation. Recording before-and-after states, masks and instructions helps locate the creative decisions involved.
Section sources: GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Sources for this account
Author or conference abstract and version record read; full proofs and experiments were not independently reproduced.
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Continue with a comparative question
Compare the methods, forms of control or presentation contexts of this entry and Learning Transferable Visual Models From Natural Language Supervision.
Compare the methods, forms of control or presentation contexts of this entry and InstructPix2Pix: Learning to Follow Image Editing Instructions.
Dates & version record
Date displayed for this node: 2021-12 · Historical date recorded for the source: 2021-12
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Original sources & further reading
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GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
https://arxiv.org/abs/2112.10741
Current cited URL
Provenance, translation & verification
Timeline entry #128 · Historical node
Research materials & supplement references · 3
AI Art Genealogy Research Master · p. 24 · 079
Date as recorded: 2021-12
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
GenAI Visual Release Chronology Research Master · p. 3 · R009
Date as recorded: 2021-12
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗
GLIDE
GenAI Visual Release Chronology Research Master · p. 3 · R011
Date as recorded: 2021-12
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗
OpenAI GLIDE
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Cite this node
ANTI-AI ARCHIVE. GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. Art-history node #128. https://salondesrefuses.cn/en/art-history/079
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