How Diffusion Models Learn to Factorize and Compose

23 August 2024

Papers citing "How Diffusion Models Learn to Factorize and Compose"

6 / 6 papers shown

Title
Concept Lancet: Image Editing with Compositional Representation Transplant Jinqi Luo Tianjiao Ding Kwan Ho Ryan Chan Hancheng Min Chris Callison-Burch René Vidal DiffM KELM 69 0 0 03 Apr 2025
CoInD: Enabling Logical Compositions in Diffusion Models Sachit Gaudi Gautam Sreekumar Vishnu Naresh Boddeti CoGe 70 0 0 03 Mar 2025
Compositional Generalization Requires More Than Disentangled Representations Qiyao Liang Daoyuan Qian Liu Ziyin Ila Fiete DRL OCL CoGe 132 0 0 30 Jan 2025
Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance Dongmin Park Sebin Kim Taehong Moon Minkyu Kim Kangwook Lee Jaewoong Cho DiffM CoGe 62 2 0 08 Jan 2025
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory Andrea Perin Stéphane Deny 88 1 0 16 Dec 2024
Compositional Generalization in Unsupervised Compositional Representation Learning: A Study on Disentanglement and Emergent Language Zhenlin Xu Marc Niethammer Colin Raffel CoGe OOD OCL DRL 39 38 0 02 Oct 2022