Tag: Diffusion Models
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Vision-Language Diffusion Models for GUI Grounding
Explore how discrete diffusion vision-language models improve GUI grounding accuracy and reduce latency in multimodal AI applications.
SPARE: Efficient Self-Distillation for Model Unlearning
Discover SPARE, a two-stage self-distillation method for efficient unlearning in image generation models, balancing forgetting and retention effectively.
Uni-DAD: Fast Few-Shot Image Generation with Diffusion Models
Uni-DAD unifies distillation and adaptation in diffusion models for rapid, high-quality few-shot image generation with improved diversity and stability.
PromptLoop: Advanced Prompt Refinement for Diffusion Models
Discover PromptLoop, a novel framework using latent feedback to refine prompts and improve diffusion model alignment with minimal overhead.
SEGAR: Enhancing Generative Augmented Reality for AR Apps
Discover SEGAR, a framework boosting augmented reality with selective enhancement and real-time correction for safer, coherent AR experiences.