Conditional Diffusion Models

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20 papers in the last four weeks, up 233% on the four weeks before. 0.2% of all new papers.

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DuET: Dual Expert Trajectories for Diffusion Image Editing
Jun 11, 2026Lidia Troeshestova, Alexander Ustyuzhanin, Sergey KastryulinText-Guided Image Editing Diffusion-Based Image Editing
HSE University · Yandex
DiffCold: A Diffusion-based Generative Model for Cold-Start Item Recommendation
Jun 10, 2026Kangning Zhang, Yingjie Qin, Weinan Zhang +2Cold-Start Recommendation Recommender Systems
Shanghai Jiao Tong University, Shanghai, China · Xiaohongshu Inc., Shanghai, China
Flow Matching with In-Context Priors for Out-of-Distribution Brain Dynamics
Jun 10, 2026Sam Gijsen, Michał Łukomski, Marc-André Schulz +1Diffusion Transformer Time Series Generation
Hertie Institute for AI in Brain Health, University of Tübingen, Germany · Tübingen AI Center, University of Tübingen, Germany · Charité – Universitätsmedizin Berlin, Department of Psychiatry and Psychotherapy, Germany +1
Cranio-Diff: Diffusion-based Cross-domain Craniofacial Reconstruction with 2D X-ray Skull Guidance and Structural Identity Constraints
Jun 8, 2026Ravi Shankar Prasad, Naresh Gurjar, Shashank Baghel +2Cross-Modal Alignment Conditional Diffusion Models
School of Computing and Electrical Engineering Indian Institute of Technology Mandi Himachal Pradesh, India · University Teaching Department, CSVTU Bhilai, India
Improving Bayesian Optimization via Training-Aware Conditional Diffusion Models
Jun 7, 2026Yilin Zheng, Haowei Wang, Szu Hui Ng +1Bayesian Optimization Black-Box Optimization
National University of Singapore · Singapore · Georgia Institute of Technology +1
Property-Informed Diffusion-Based Text-to-Microstructure Generation
Jun 6, 2026Bingxuan Dai, Hongsong Wang, Jie GuiMaterials Science Conditional Diffusion Models
School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China · School of Computer Science and Engineering, Southeast University, Nanjing 210096, China · Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China +2
Diff-CA: Separating Common and Salient Factors with Diffusion Models
Jun 4, 2026Michaël Soumm, Alexandre Fournier Montgieux, Yunlong He +2Disentangled Representation Learning Diffusion-Based Image Editing
INRIA at Univ. Grenoble Alpes · CEA List, Palaiseau · Télécom Paris, Institut Polytechnique de Paris
FontFusion: Enhancing Generative Text in Diffusion Models with Typographic Conditioning
Jun 4, 2026Marian Lupascu, Nipun Jindal, Ionut Mironica +1Conditional Image Generation T2I Generation
Adobe Research · Department of Computer Science, University of Bucharest, Romania
Diffusion Models for Adaptive Sequential Data Generation
Jun 4, 2026Haoyang Cao, Minshuo Chen, Yinbin Han +1Time Series Generation Conditional Diffusion Models
Department of Applied Mathematics and Statistics, Data Science and AI Institute, and Mathematical Institute for Data Science, Johns Hopkins University. · Department of Industrial Engineering and Management Sciences, Northwestern University. · Department Management Science and Engineering, Stanford University.
CoFi-UCGen: Coarse-to-Fine Unsupervised Conditional Generation without Label Priors
Jun 4, 2026Shengxi Li, Zhaokun Hu, Ce Zheng +3Disentangled Representation Learning Conditional Image Generation
Department of Electronic Information Engineering, Beihang University, Beijing 100191, China · School of Cyber Science and Technology, Beihang University, Beijing 100191, China · College of Electronic Science, National University of Defense Technology, Hunan 410073, China +1
DiffUNet^2: Bidirectional Conditional Diffusion for Probabilistic Scientific Spatiotemporal Modeling
Jun 2, 2026Mengdi Chu, Jiaxin Yang, Angus G. Forbes +4Diffusion Model Guidance Probabilistic Forecasting
Mengdi Chu, Jiaxin Yang, and Han-Wei Shen are with the Ohio State University. · Angus G. Forbes is with NVIDIA. · Nathan Debardeleben, Earl Lawrence, Ayan Biswas are with Los Alamos National Laboratory.
Conditional Latent Diffusion Model with Fourier-based Motion Modelling for Virtual Population Synthesis
Jun 2, 2026Shaokun Lan, Haoran Dou, Jinghan Huang +53D Mesh Generation Conditional Diffusion Models
Centre for Computational Imaging and Modelling in Medicine (CIMIM), University of Manchester, Manchester, UK
Diffusion-Based Heart Sound Generation: Evaluation with Physiological Signal Metrics, Classifiers, and Expert Listening
Jun 1, 2026Xinqi Bao, Jia Bi, Xin Chen +2Audio Diffusion Models Conditional Diffusion Models
Department of Information Science & Engineering, KTH Royal Institute of Technology, Stockholm, 114 28 Sweden · Karolinska Institutet (KI), Stockholm, Sweden · Rutherford Appleton Laboratory, United Kingdom +2
Genotype-Conditioned Molecular Generation via Evidence-Grounded Multi-Objective Latent Perturbation in Diffusion Models
May 31, 2026Brenda Nogueira, Gisela A. Gonzalez-Montiel, Nitesh V. Chawla +1Molecular Optimization Oncology
Department of Computer Science and Engineering University of Notre Dame Notre Dame, IN, 46556 · Department of Chemistry and Biochemistry University of Notre Dame Notre Dame, IN, 46556 · Lucy Family Institute for Data & Society University of Notre Dame Notre Dame, IN, 46556
DiffuSent: Towards a Unified Diffusion Framework for Aspect-Based Sentiment Analysis
May 31, 2026Shu Long, Yanglei Gan, Xuchuan ZhouAspect-Based Sentiment Analysis Conditional Diffusion Models
University of Electronic Science and Technology of China · Southwest Petroleum University · Southwest Minzu University
GLIDE: Graph-guided Leap Inference for Diffusion Estimation of Spatio-Temporal Point Processes
May 31, 2026Guanyu Zhou, Yao Liu, Yanglei Gan +5Event Time Prediction Temporal Point Processes
University of Electronic Science and Technology of China, Chengdu, China
Cross-Axis Feature Fusion with Joint-Wise Motion Difference Prediction for Text-Based 3D Human Motion Editing
May 31, 2026Gyojin Han, Junmo KimHuman Motion Generation Conditional Diffusion Models
School of Electrical Engineering, KAIST
COLLAR: Cascaded Object-Level Latent Refinement for High-Fidelity Conditional Generation
May 31, 2026Xinlong Zhang, Jia Wei, Xiaoyu Zhang +3Diffusion Transformer Conditional Diffusion Models
College of Computer Science Zhejiang University Hangzhou, Zhejiang, China
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.
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
Treatment-Conditioned Diffusion for Forecasting Neurodegenerative Disease Progression
May 28, 2026Danylo Boiko, Viktoriia MishkurovaLongitudinal Medical Image Analysis Clinical Outcome Prediction
Innoloft Inc. 701 Brazos Street, Austin, TX 78701, USA · Bogomolets National Medical University Beresteiskyi Avenue, 34, Kyiv, 03057, Ukraine
DC-Motion: Decoupling Structure and Details via Discrete-Continuous Tokens for Human Motion Generation
May 28, 2026Hequan Wang, Xuean Chen, Jiaxu Zhang +2Text-to-Motion Generation Human Motion Generation
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China · Geophysical Exploration Brigade of Hubei Provincial Geological Bureau, Wuhan 430058, China · Information Systems Technology and Design Pillar, Singapore University of Technology and Design, 487372, Singapore
Three-dimensional Conditional Diffusion Models for Cosmological 21 cm Lightcone Emulation
May 27, 2026Bin Xia, John H. WiseConditional Diffusion Models
Center for Relativistic Astrophysics, School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA
Inpainting-Style Conditional Diffusion for Multivariable Time Series Forecasting
May 27, 2026Kourosh Kiani, S. M. MuyeenMultivariate Time Series Forecasting Time Series Forecasting
1Electrical and Computer Engineering, Semnan University, Semnan, Iran · Electrical Engineering Department, Qatar University, Doha, Qatar
Towards Controllable Image Generation through Representation-Conditioned Diffusion Models
May 26, 2026Nithesh Chandher Karthikeyan, Jonas Unger, Gabriel EilertsenDiffusion-Based Image Generation Conditional Diffusion Models
Linköping University, Norrköping, Sweden
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
High-Quality Synthetic Financial Time-Series using a GAN-Diffusion Framework
May 26, 2026Giuseppe Masi, Andrea Coletta, Novella BartoliniSynthetic Data Generation Time Series Generation
Sapienza University of Rome, Italy · Banca d’Italia, Italy
Scheduled Style Injection: Expanding the Style-Content Pareto Frontier in Training-Free Diffusion-based Style Transfer
May 26, 2026Amey Sunil KulkarniDiffusion Model Guidance Image Style Transfer
Independent Researcher
EMA: Effort Metric Attention for Anatomical Effort-Guided Human Motion Diffusion
May 23, 2026Joshua Siy, Huakun Liu, Yutaro Hirao +3Human Motion Generation Conditional Diffusion Models
Nara Institute of Science and Technology, Ikoma, Nara, Japan
Diffusion Domain Expansion: Learning to Coordinate Pre-trained Diffusion Models
May 22, 2026Egor Lifar, Semyon Savkin, Timur Garipov +2Diffusion-Based Image Generation Conditional Diffusion Models
MIT CSAIL, Cambridge, USA

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DuET: Dual Expert Trajectories for Diffusion Image Editing

Lidia Troeshestova, Alexander Ustyuzhanin, Sergey Kastryulin

HSE University · Yandex

Text-Guided Image Editing Diffusion-Based Image Editing Conditional Diffusion Models

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Recent diffusion editors perform diverse instruction-based edits while conditioning on the source image at every denoising step. Yet persistent source-image conditioning can limit how fully an edit is executed and how natural the result appears, especially when the target scene diverges substantially from the input. We introduce DuET (Dual Expert Trajectories), a training-free inference method that temporarily relaxes source-image conditioning by transitioning through a text-to-image phase before returning to edit mode, allowing the denoising trajectory to move toward the target distribution while retaining the structural benefits of image-conditioned editing. Without modifying model weights or increasing sampling cost, DuET consistently improves instruction relevance, semantic fidelity, and perceptual quality across diverse models and benchmarks. In some cases, these gains come with a modest reduction in source-image preservation, revealing a predictable trade-off between source preservation and edit fidelity.

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