Diffusion Models

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Overview

Diffusion models learn a data distribution by gradually corrupting examples with noise and training a denoiser to reverse that process. Major approaches include DDPMs and score-based SDEs, latent diffusion and diffusion Transformers, flow and consistency methods, and discrete masked or continuous-time Markov diffusion; conditioning and guidance adapt them to specific tasks. They are used for images, video, audio, language, molecules, and scientific forecasting, with evaluations ranging from ImageNet FID to language perplexity and domain-specific measures of accuracy and uncertainty. A central tension is how to make sampling faster and generation more controllable without sacrificing quality, calibration, or diversity, while theory and ongoing audits address generalization, memorization, and privacy.

Latest papers

CardsList

1,192 papers152 papers in the last four weeks, up 77% on the four weeks before. 0.9% of all new papers.

  1. SemanticNVS: Improving Semantic Scene Understanding in Generative Novel View Synthesis

    Feb 23, 2026Xinya Chen, Christopher Wewer, Jiahao Xie +2Novel View SynthesisMulti-View Image Synthesis

    Max Planck Institute for Informatics, Saarland Informatics Campus, Germany

  2. Expanding the Role of Diffusion Models for Robust Classifier Training

    Feb 23, 2026Pin-Han Huang, Shang-Tse Chen, Hsuan-Tien LinAdversarial RobustnessAdversarial Training

    National Taiwan University

  3. PerturbDiff: Functional Diffusion for Single-Cell Perturbation Modeling

    Feb 23, 2026Xinyu Yuan, Xixian Liu, Ya Shi Zhang +3Single-Cell Perturbation ModelingSingle-Cell Transcriptomics

    Mila - Québec AI Institute · University of Montréal · University of Ottawa +3

  4. DICArt: Advancing Category-level Articulated Object Pose Estimation in Discrete State-Spaces

    Feb 23, 2026Li Zhang, Mingyu Mei, Ailing Wang +7Object Pose EstimationDiffusion Models

    University of Science and Technology of China · Zhejiang University · East China Normal University +6

  5. Variational Trajectory Optimization of Anisotropic Diffusion Schedules

    Feb 23, 2026Pengxi Liu, Zeyu Michael Li, Xiang ChengDiffusion ModelsDiffusion Timestep Scheduling

    Department of Electrical and Computer Engineering, Duke University

  6. Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control

    Feb 23, 2026Shaorong Chen, Jingbo Zhou, Jun XiaMass SpectrometryDiffusion Model Guidance

    Zhejiang University, Hangzhou, China, 310058 · AI Lab, Westlake University, Hangzhou, China, 310030 · AIMS Lab, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China, 511453 +1

  7. VLM-Guided Group Preference Alignment for Diffusion-based Human Mesh Recovery

    Feb 22, 2026Wenhao Shen, Hao Wang, Wanqi Yin +5Human Mesh Recovery3D Human Reconstruction

    Nanyang Technological University · HKUST(GZ) · SenseTime Research +1

  8. Insertion Based Sequence Generation with Learnable Order Dynamics

    Feb 21, 2026Dhruvesh Patel, Benjamin Rozonoyer, Gaurav Pandey +3Diffusion ModelsMasked Diffusion Models

    University of Massachusetts Amherst · IBM Research

  9. The Geometry of Noise: Why Diffusion Models Don't Need Noise Conditioning

    Feb 20, 2026Mojtaba Sahraee-Ardakan, Mauricio Delbracio, Peyman MilanfarDiffusion ModelsDiffusion Sampling

    Google

  10. Annealed Co-Generation: Disentangling Variables via Progressive Pairwise Modeling

    Feb 20, 2026Hantao Zhang, Jieke Wu, Mingda Xu +3Generative ModelingDiffusion Models

    CVLab, EPFL

  11. Correlation Analysis of Generative Models

    Feb 20, 2026Zhengguo Li, Chaobing Zheng, Wei WangGenerative ModelingDiffusion Models

    VI Department, Institute for Infocomm Research, A*STAR, Singapore, 138632 · School of ISE, Wuhan University of Science and Technology, Wuhan, China · School of CST, Wuhan University of Science and Technology, Wuhan, China

  12. Two Calm Ends and the Wild Middle: A Geometric Picture of Memorization in Diffusion Models

    Feb 19, 2026Nick Dodson, Xinyu Gao, Qingsong Wang +2Memorization in Generative ModelsDiffusion Models

    Department of Mathematics, University of Missouri, Columbia, Missouri, USA · Halıcıo˘glu Data Science Institute, University of California San Diego, La Jolla, California, USA

  13. MolHIT: Advancing Molecular-Graph Generation with Hierarchical Discrete Diffusion Models

    Feb 19, 2026Hojung Jung, Rodrigo Hormazabal, Jaehyeong Jo +5Molecular Graph GenerationDiffusion Models

    KAIST AI · LG AI Research · Seoul National University

  14. Unified Latents (UL): How to train your latents

    Feb 19, 2026Jonathan Heek, Emiel Hoogeboom, Thomas Mensink +1Diffusion AutoencoderLatent Diffusion Models

    Google DeepMind Amsterdam

  15. Unpaired Image-to-Image Translation via a Self-Supervised Semantic Bridge

    Feb 18, 2026Jiaming Liu, Felix Petersen, Yunhe Gao +6Unpaired Image-to-Image TranslationDiffusion Models

    Stanford University · LLNL · Johns Hopkins University

  16. Quantifying Error Propagation and Model Collapse in Diffusion Models

    Feb 18, 2026Nail B. Khelifa, Richard E. Turner, Ramji VenkataramananModel CollapseDiffusion Models

    University of Cambridge, Cambridge, United Kingdom.

  17. Steering diffusion models with quadratic rewards: a fine-grained analysis

    Feb 18, 2026Ankur Moitra, Andrej Risteski, Dhruv RohatgiDiffusion SamplingDiffusion Models

  18. Fast and Scalable Analytical Diffusion

    Feb 18, 2026Xinyi Shang, Peng Sun, Jingyu Lin +1Diffusion ModelsDiffusion Model Inference Acceleration

    University College London · Mohamed bin Zayed University of Artificial Intelligence · Zhejiang University +2

  19. Training-Free Adaptation of Diffusion Models via Doob's hh-Transform

    Feb 18, 2026Qijie Zhu, Zeqi Ye, Han Liu +2Diffusion Model AdaptationDiffusion Models

    Department of Statistics and Data Science, Northwestern University. · Department of Industrial Engineering and Management Sciences, Northwestern University. · Department of Computer Science, Northwestern University.

  20. GlobeDiff: State Diffusion Process for Partial Observability in Multi-Agent Systems

    Feb 17, 2026Yiqin Yang, Xu Yang, Yuhua Jiang +8Multi-Agent SystemsDiffusion Models

    The Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences · Tsinghua University · Moonshot AI +2

  21. Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits

    Feb 17, 2026Gilad Nurko, Roi Benita, Yehoshua Dissen +4Robust ClassificationDiffusion Models

    Technion – Israel Institute of Technology, Haifa, Israel · NTT, Inc., Japan.

  22. Efficient Generative Modeling beyond Memoryless Diffusion via Adjoint Schrödinger Bridge Matching

    Feb 17, 2026Jeongwoo Shin, Jinhwan Sul, Joonseok Lee +2Diffusion Model SamplingSchrödinger Bridges

    Seoul National University, Seoul, Korea · Georgia Institute of Technology, Atlanta, GA, USA · Sungkyunkwan University, Seoul, Korea

  23. Steering Dynamical Regimes of Diffusion Models by Breaking Detailed Balance

    Feb 17, 2026Haiqi Lu, Ying TangDiffusion ModelsDiffusion Sampling

    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China · Yingcai Honor College, University of Electronic Science and Technology of China, Chengdu 611731, China · School of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China +2

  24. Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation

    Feb 16, 2026Cai Zhou, Zijie Chen, Zian Li +7Generative ModelingDiffusion Models

    Massachusetts Institute of Technology · Zhejiang University · Peking University +3

  25. Scaling Beyond Masked Diffusion Language Models

    Feb 16, 2026Subham Sekhar Sahoo, Jean-Marie Lemercier, Zhihan Yang +4Diffusion Language ModelsDiffusion Models

    NVIDIA, Santa Clara, USA · Department of Computer Science, Cornell Tech, NYC, USA · Department of Computer Science, Cornell University, Ithaca, USA +2

  26. Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees

    Feb 16, 2026Daniil Dmitriev, Zhihan Huang, Yuting WeiSample ComplexityDiffusion Model Sampling

    Department of Statistics and Data Science, the Wharton School, University of Pennsylvania

  27. High-Resolution Climate Projections Using Diffusion-Based Downscaling of a Lightweight Climate Emulator

    Feb 13, 2026Haiwen Guan, Dibyajyoti Chakraborty, Moein Darman +3Climate ScienceClimate Modeling

    1Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania · Department of Applied Mathematics, University of California, Santa Cruz, California · 3Allen Institute for Artificial Intelligence (AI2), Seattle, Washington +1

  28. ELROND: Exploring and decomposing intrinsic capabilities of diffusion models

    Feb 10, 2026Paweł Skierś, Emilia Kaczmarczyk, Tomasz Trzciński +1Diffusion ModelsT2I Diffusion Models

    Warsaw University of Technology · IDEAS Research Institute

  29. Improved Sampling Schedules for Discrete Diffusion Models

    Feb 6, 2026Alberto Foresti, Mustapha Bounoua, Giulio Franzese +2Diffusion SamplingDiffusion Models

    Department of Data Science, EURECOM, 450 Route des Chappes, 06410 Biot, France · Donders Institute for Brain, Cognition and Behaviour, Radboud University, Postbus 9102, 6500 HC Nijmegen, Netherlands

  30. Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design

    Feb 4, 2026Jaemoo Choi, Yuchen Zhu, Wei Guo +6T2I GenerationDiffusion Model Fine-Tuning

    Georgia Institute of Technology · National University of Singapore · Nanjing university.