Latent Diffusion Models

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9 papers in the last four weeks, up 13% on the four weeks before. 0.1% of all new papers.

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Learning When to Denoise: Optimizing Asynchronous Schedules for Latent Diffusion
Jun 18, 2026Bingshuo Qian, Xiang ChengFlow Matching Latent Diffusion Models
Department of Electrical and Computer Engineering Duke University
BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation
Jun 17, 2026Max Van Puyvelde, Ibrahim Gulluk, Wim Van Criekinge +1Masked Autoencoders Latent Diffusion Models
Department of Biomedical Data Science, Stanford University School of Medicine · Department of Mathematical Modelling, Statistics & Bioinformatics, Ghent University · Department of Electrical Engineering, Stanford University
The Market in the Model: Latent Diffusion as Neural Economy
Jun 17, 2026Eryk SalvaggioLatent Diffusion Models Diffusion-Based Image Generation
Cambridge Digital Humanities, University of Cambridge · Machine Visual Culture Research Group, Max Planck Institute
MUNI: Multimodal Unified Latent Diffusion for Coherent Any-to-Any Generation
Jun 15, 2026Kyeongmin Yeo, Yunhong Min, Minhyuk SungLatent Diffusion Models Multimodal Generation
KAIST
Structure-Semantic Co-optimized Latent Diffusion Model for Fast Visual Anagram Synthesis
Jun 15, 2026Xiang Gao, Yunpeng JiaLatent Diffusion Models Image Generation
School of Digital Media and Design Arts Beijing University of Posts and Telecommunications
Smoothing Dark Areas in Molecular Latent Diffusion
Jun 11, 2026Xi Wang, Jiahan Li, Yuxuan Xia +3Variational Autoencoders Latent Diffusion Models
New York University · Stanford University
Diffusion Transformer World-Action Model for AV Scene Prediction
Jun 11, 2026Ruslan Sharifullin, Benjamin Jiang, Kai Xi ChewAction-Conditioned Video Generation Diffusion Transformer
Stanford University
VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models
Jun 10, 2026Chunlin Qiu, Ang Li, Tianxiao Huang +7Latent Diffusion Models Image Generation
School of Cyber Science and Engineering, Wuhan University · School of Computer Science, Wuhan University · Institute for Math&AI, Wuhan University +2
Data assimilation for subsurface flow using latent diffusion model parameterization: performance of ensemble-Kalman and Monte Carlo techniques
Jun 9, 2026Guido Di Federico, Wenchao Teng, Louis J. DurlofskyMarkov Chain Monte Carlo Latent Diffusion Models
Department of Energy Science & Engineering, Stanford University, Stanford, CA, 94305, USA
Echo-DM: Ultrasound Marker Removal via Conditional Latent Diffusion and Region-Aware Fusion
Jun 8, 2026Zhiwei Wang, Tao Huang, Wentao Jiang +7Diffusion Models for Image Restoration Latent Diffusion Models
School of Computer Science, Wuhan University, China · The Central Hospital of Wuhan, China · School of Computer Science, Hubei University of Technology, China
Continuous Language Diffusion as a Decoder-Interface Problem
Jun 7, 2026Zhicheng Du, Lan MaLatent Diffusion Models Diffusion Language Model Decoding
Tsinghua Shenzhen International Graduate School, Tsinghua University
Bypassing Copyright Protection in Diffusion-based Customization via Two-Stage Latent Feature Optimization
Jun 6, 2026Ziang Xu, Wenbo Yu, Hongyao Yu +6Latent Diffusion Models Adversarial Attacks
Harbin Institute of Technology, Shenzhen Shenzhen, Guangdong, China · Tsinghua Shenzhen International Graduate School Shenzhen, Guangdong, China
TargetSEC: Plug-and-Play In-the-Wild Speech Emotion Conversion via Arousal-Conditioned Latent Style Diffusion
Jun 5, 2026Constantin Alexander AugaLatent Diffusion Models Audio Diffusion Models
Hasso Plattner Institute / University of Potsdam, Potsdam, Germany
ARAPDiffusion: ARAP Regularization for Diffusion-Based Deformable Shape Space Learning
Jun 5, 2026Haibo Liu, Jinghan Ke, Haitao Yang +3Latent Diffusion Models 3D Shape Generation
University of Texas at Austin · 2Westlake University
Reflection Separation from a Single Image via Joint Latent Diffusion
Jun 2, 2026Zheng-Hui Huang, Zhixiang Wang, Yu-Lun Liu +1Diffusion Models for Image Restoration Latent Diffusion Models
Shanda AI Research Tokyo · National Yang Ming Chiao Tung University · National Taiwan University
Diffusing in the Right Space: A Systematic Study of Latent Diffusability
Jun 2, 2026Tianxiong Zhong, Xingye Tian, Xuebo Wang +2Latent Diffusion Models Image Tokenization
Kling Team, Kuaishou Technology
Improving Combined Detection and Classification of TEM Defects via Mask-Conditioned Latent Diffusion Augmentation
Jun 1, 2026Ni Li, Nuohao Liu, Ryan Jacobs +5Synthetic Data Augmentation Latent Diffusion Models
University of Wisconsin-Madison, Madison, WI · University of Michigan-Ann Arbor, Ann Arbor, MI
DeblurNVS: Geometric Latent Diffusion for Novel View Synthesis from Sparse Motion-Blurred Images
May 31, 2026Changyue Shi, Wangbo Yu, Chaoran Feng +1Latent Diffusion Models 3D Reconstruction
School of AI for Science, Peking University Shenzhen Graduate School, Shenzhen, 518055 China · School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, 518055 China
Data Enrichment for Symbolic Regression Using Diffusion Models
May 31, 2026Simon De Reuver, Tamas Kristof Toth, Teddy LazebnikPhysics-Informed Diffusion Models Physics-Informed Generative Modeling
Department of Computing, Jönköping University, Jönköping, Sweden · Department of Information Science, University of Haifa, Haifa, Israel
Latent Diffusion Pretraining for Crystal Property Prediction
May 30, 2026Shrimon Mukherjee, Kishalay Das, Partha Basuchowdhuri +2Latent Diffusion Models Self-Supervised Pre-Training
School of Mathematical & Computational Sciences, Indian Association for the Cultivation of Science, Kolkata, India · Computer Science and Engineering, Indian Institute of Technology Kharagpur, India.
Wavelet-Fusion Diffusion Model for Multimodal Brain MRI Synthesis with Modality and Metadata Conditioning
May 30, 2026Muhammad Nabi Yasinzai, Remika Mito, Mangor PedersenVariational Autoencoders Latent Diffusion Models
Department of Psychology & Neuroscience, Auckland University of Technology, Auckland, New Zealand. · Department of Psychiatry, University of Melbourne, Melbourne, Victoria 3053, Australia. · Auckland University of Technology, Auckland, New Zealand.
UNISON: A Unified Sound Generation and Editing Framework via Deep LLM Fusion
May 29, 2026Zhaoqing Li, Haoning Xu, Jingran Su +9Text-to-Audio Generation TTS Synthesis
The Chinese University of Hong Kong · The Hong Kong Polytechnic University · City University of Hong Kong +3
DiffCrossGait: Trajectory-Level Alignment for 2D-3D Cross-Modal Gait Recognition via Latent Diffusion
May 29, 2026Zhiyang Lu, Ming ChengDiffusion Model Alignment Latent Diffusion Models
1Fujian Key Laboratory of Urban Intelligent Sensing and Com · 2Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Min
Controllable Lung Nodule Synthesis via Histogram-Regularized Latent Diffusion Models
May 28, 2026Arunkumar Kannan, Yanbo Zhang, Han Liu +5Synthetic Data Augmentation Latent Diffusion Models
aDigital Technology and Innovation, Siemens Healthineers, Princeton, NJ, USA · bJohns Hopkins University, Baltimore, MD, USA · cDigital Technology and Innovation, Siemens Healthineers, Erlangen, Germany +1
Latent Diffusion for Missing Data
May 27, 2026Alberte Heering Estad, Ignacio Peis, Jes FrellsenIncomplete Data Imputation Latent Diffusion Models
Technical University of Denmark · Pioneer Centre for Artificial Intelligence
PhAME: Phenotype-Aware Molecular Editing via Latent Diffusion
May 27, 2026Łukasz Janisiów, Sebastian Musiał, Bartosz Zieliński +2Molecular Optimization Classifier-Free Guidance
Faculty of Mathematics and Computer Science, Jagiellonian University · Doctoral School of Exact and Natural Sciences, Jagiellonian University · Jagiellonian Center for Artificial Intelligence, Jagiellonian University +2
Representation-Conditioned Diffusion Models for Guided Training Data Generation
May 26, 2026Nithesh Chandher Karthikeyan, Jonas Unger, Gabriel EilertsenSynthetic Data Augmentation Latent Diffusion Models
Linkoping University
Diffusion-Based Ukrainian Handwritten Text Generation with Cross-Domain Style Transfer
May 26, 2026Andrii Ahitoliev, Pavlo BerezinLatent Diffusion Models Image Style Transfer
Ukrainian Catholic University, Lviv, Ukraine · National University of “Kyiv-Mohyla Academy”, Kyiv, Ukraine
Equivalent Flows, Unequal Learning: Clean-Latent Prediction in Transformers
May 26, 2026Funing Fu, Tenghui Wang, Guanyu Zhou +2Flow Matching Diffusion Transformer
Independent Researcher · Wuhan University of Technology · Hangzhou Jiyi Artificial Intelligence Co., Ltd.
DGLD: Domain-Gated Latent Diffusion for the Discovery of Novel Energetic Materials
May 26, 2026Yehudit Aperstein, Alexander ApartsinMolecular Optimization Latent Diffusion Models
Department of Intelligent Systems, Afeka Tel-Aviv College of Engineering, Israel. · School of Computer Science, Faculty of Sciences, HIT-Holon Institute of Technology, Israel.

Jun 18, 2026, cs.CVJ/K move · Enter open · S save

Learning When to Denoise: Optimizing Asynchronous Schedules for Latent Diffusion

Bingshuo Qian, Xiang Cheng

Department of Electrical and Computer Engineering Duke University

Flow Matching Latent Diffusion Models Diffusion-Based Image Generation Diffusion Timestep Scheduling Diffusion Models

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Multi-representation diffusion models can improve visual synthesis by denoising complementary views of an image, but their performance depends critically on the asynchronous schedule that determines when each representation is denoised. We propose to learn this schedule. Our method formulates asynchronous flow matching over multiple representation spaces and uses a schedule-corrected objective that keeps each representation's local noising-time weights fixed as the schedule changes. We instantiate the schedule with a flexible parametric class that is convex and monotone by construction, and learn it using a fast joint probe with less than 1% additional training compute. On ImageNet 256x256, the learned schedule substantially improves both convergence speed and final quality under a matched 675M-parameter XL backbone. With AutoGuidance, our 200-epoch model reaches FID 1.05, matching the 800-epoch SFD-XL baseline with 4x less training. Training to 600 epochs further improves to FID 1.02, outperforming the 1B-parameter SFD-XXL result of FID 1.04 while using a smaller model. In the unguided setting, our 200-epoch model reaches FID 2.37, already below the best 800-epoch SFD-XL result (2.54) at 4x less training, and improves to FID 2.14 at 600 epochs. Code is available at https://github.com/bsq532087/LWD

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