Angusliuuu/Awesome-Controllable-Generative-Models-Papers

A curated list of recent papers (2023–2025) on controllable generative models, covering diffusion-based architectures with fine-grained control, attention interpretation, spectral manipulation, and structure-preserving image editing. Ideal for researchers and developers exploring controllable synthesis.

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This is a curated collection of the latest research papers (2023-2025) on generative AI models that allow for precise control over the output, especially focusing on diffusion models. It helps researchers stay updated on advancements in guiding AI image generation, understanding how these models interpret instructions, and editing images with high fidelity. The collection is for AI researchers, graduate students, and engineers working on developing or advancing generative AI systems.

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Use this if you are an AI researcher or developer who needs to keep pace with the bleeding edge of controllable generative models, specifically diffusion-based architectures.

Not ideal if you are a practitioner looking for ready-to-use applications of generative AI or a non-technical user.

Generative AI Research Diffusion Models Image Synthesis Machine Learning Engineering AI Model Control
No License Stale 6m No Package No Dependents
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Jun 27, 2025

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