4 papers
Latent Structure Emergence in Diffusion Models via Confidence-Based Filtering
Wei Wei, Yizhou Zeng, Kuntian Chen +3
Diffusion models rely on a high-dimensional latent space of initial noise seeds, yet it remains unclear whether this space contains sufficient structure to predict properties of th…
QoSDiff: An Implicit Topological Embedding Learning Framework Leveraging Denoising Diffusion and Adversarial Attention for Robust QoS Prediction
Guanchen Du, Jianlong Xu, Wei Wei
Accurate Quality of Service (QoS) prediction is fundamental to service computing, providing essential data-driven guidance for service selection and ensuring superior user experien…
Delta Sampling: Data-Free Knowledge Transfer Across Diffusion Models
Zhidong Gao, Zimeng Pan, Yuhang Yao +2
Diffusion models like Stable Diffusion (SD) drive a vibrant open-source ecosystem including fully fine-tuned checkpoints and parameter-efficient adapters such as LoRA, LyCORIS, and…
Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled yet Hard-to-Learn Samples in Noisy Data
Weiran Pan, Wei Wei, Feida Zhu +1
We propose a novel sample selection method for image classification in the presence of noisy labels. Existing methods typically consider small-loss samples as correctly labeled. Ho…