From the 1 of 10 linked papers with an AI index.
10 papers
Heavy-Tailed Flow Matching via Random Clocks
Zhouhao Yang, Yezhen Wang, Kenji Kawaguchi +2
The paper introduces Heavy-Tailed Flow Matching via Random Clocks (HTFM), a method that models heavy‑tailed source distributions as mixtures of Gaussian flows conditioned on random…
Learnable Sparsity for Vision Generative Models
Yang Zhang, Er Jin, Wenzhong Liang +5
Diffusion models have achieved impressive advancements in various vision tasks. However, these gains often rely on increasing model size, which escalates computational complexity a…
DeRaDiff: Denoising Time Realignment of Diffusion Models
Ratnavibusena Don Shahain Manujith, Teoh Tze Tzun, Kenji Kawaguchi +1
Recent advances align diffusion models with human preferences to increase aesthetic appeal and mitigate artifacts and biases. Such methods aim to maximize a conditional output dist…
Unconsciously Forget: Mitigating Memorization; Without Knowing What is being Memorized
Er Jin, Yang Zhang, Yongli Mou +4
Recent advances in generative models have demonstrated an exceptional ability to produce highly realistic images. However, previous studies show that generated images often resembl…
Minimalist Concept Erasure in Generative Models
Yang Zhang, Er Jin, Yanfei Dong +5
Recent advances in generative models have demonstrated remarkable capabilities in producing high-quality images, but their reliance on large-scale unlabeled data has raised signifi…
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization
Qianli Shen, Yezhen Wang, Zhouhao Yang +6
Bi-level optimization (BO) has become a fundamental mathematical framework for addressing hierarchical machine learning problems. As deep learning models continue to grow in size,…