Flow-Based Generative Modeling

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Overview

Flow-based generative modeling represents generation as a transformation of probability mass, often by integrating a continuous-time velocity field from noise to data or composing invertible normalizing-flow layers. Flow matching and rectified flow train velocity fields by regression along selected paths; optimal-transport couplings, stochastic interpolants, discrete Markov flows, and flow maps extend the toolkit to different data types and sampling budgets. Researchers apply these methods to images, language, molecules, physical fields, and robot actions, assessing fidelity and diversity alongside likelihood, constraint satisfaction, calibration, and runtime. A central challenge is achieving one- or few-step generation without sacrificing quality or mode coverage, while improving path design, robustness, geometric and physical consistency, and theoretical guarantees.

Latest papers

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563 papers125 papers in the last four weeks, up 131% on the four weeks before. 0.7% of all new papers.

  1. Generative Inverse Design with Abstention via Diagonal Flow Matching

    Mar 16, 2026Miguel de Campos, Werner Krebs, Hanno GottschalkFlow MatchingUncertainty Quantification

    Institute of Mathematics, TU Berlin · Siemens Energy

  2. Conditional Rectified Flow-based End-to-End Rapid Seismic Inversion Method

    Mar 16, 2026Haofei Xu, Wei Cheng, Sizhe Li +1Inverse ProblemsConditional Generative Modeling

    School of Electronic lnformation and Electrical Engineering, Yangtze UniversityJingzhou, Hubei 434023, PR.China

  3. Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling

    Mar 16, 2026Aram Davtyan, Leello Tadesse Dadi, Volkan Cevher +1Flow-Based Generative ModelingConditional Flow Matching

    University of Bern, Bern, Switzerland · EPFL, Lausanne, Switzerland

  4. TrajFlow: Nation-wide Pseudo GPS Trajectory Generation with Flow Matching Models

    Mar 16, 2026Peiran Li, Jiawei Wang, Haoran Zhang +4Trajectory GenerationFlow-Based Generative Modeling

    Hitotsubashi University · The University of Tokyo · LocationMind Inc. +1

  5. AR-Flow VAE: A Structured Autoregressive Flow Prior Variational Autoencoder for Unsupervised Blind Source Separation

    Mar 15, 2026Yuan-Hao Wei, Fu-Hao Deng, Lin-Yong Cui +1Variational AutoencodersFlow-Based Generative Modeling

    Hong Kong Polytechnic University · Wuhan University of Technology · The University of Hong Kong

  6. GoldenStart: Q-Guided Priors and Entropy Control for Distilling Flow Policies

    Mar 15, 2026He Zhang, Ying Sun, Hui XiongPolicy DistillationContinuous Control

    Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou) · AI2 Robotics · Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR

  7. Discriminative Flow Matching Via Local Generative Predictors

    Mar 14, 2026Om Govind Jha, Manoj Bamniya, Ayon BorthakurFlow MatchingObject Detection

    Indian Institute of Science Education and Research Bhopal, India · Indian Institute of Technology Guwahati, India

  8. KoopmanFlow: Spectrally Decoupled Generative Control Policy via Koopman Structural Bias

    Mar 14, 2026Chengsi Yao, Ge Wang, Kai Kang +9Robotic ManipulationFlow-Based Generative Modeling

    ISing AI · Future Network of Intelligence Institution, The Chinese University of Hong Kong, Shenzhen · Guangdong Polytechnic Normal University +1

  9. 3DTCR: Vortex-following generative reconstruction improves tropical cyclone intensity prediction from global AI weather forecasts

    Mar 13, 2026Jun Liu, Xiaohui Zhong, Kai Zheng +5Tropical Cyclone Intensity ForecastingWeather Forecasting

    Artificial Intelligence Innovation and Incubation Institute, Fudan University, Shanghai, 200433, China. · Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200438, China. · Shanghai Academy of Artificial Intelligence for Science, Shanghai, 200232, China.

  10. Improving Channel Estimation via Multimodal Diffusion Models with Flow Matching

    Mar 13, 2026Xiaotian Fan, Xingyu Zhou, Le Liang +2Channel EstimationMultimodal Diffusion Models

    School of Information Science and Engineering, Southeast University, Nanjing 210096, China · Purple Mountain Laboratories, Nanjing 211111, China

  11. VGGT-World: Transforming VGGT into an Autoregressive Geometry World Model

    Mar 13, 2026Xiangyu Sun, Shijie Wang, Fengyi Zhang +53D Scene PredictionWorld Model Learning

    UQMM Lab, The University of Queensland · Beijing Jiaotong University

  12. From Sparse to Dense: Multi-View GRPO for Flow Models via Augmented Condition Space

    Mar 13, 2026Jiazi Bu, Pengyang Ling, Yujie Zhou +8RL for Image GenerationGroup Relative Policy Optimization

    Shanghai Jiao Tong University · S-Lab, Nanyang Technological University · Shanghai AI Laboratory +7

  13. Curriculum Sampling: A Two-Phase Curriculum for Efficient Training of Flow Matching

    Mar 12, 2026Pengwei SunFlow MatchingFlow-Based Generative Modeling

    Stanford University

  14. One-Step Flow Policy: Self-Distillation for Fast Visuomotor Policies

    Mar 12, 2026Shaolong Li, Lichao Sun, Yongchao ChenVisuomotor Policy LearningOne-Step Generative Modeling

    CSE Department, University of Michigan · Lehigh University · College of AI, Tsinghua University

  15. Generalization and Memorization in Rectified Flow

    Mar 12, 2026Mingxing Rao, Daniel MoyerRectified FlowMembership Inference Attacks

    Vanderbilt University, Nashville TN 37235, USA

  16. Sinkhorn-Drifting Generative Models

    Mar 12, 2026Ping He, Om Khangaonkar, Hamed Pirsiavash +2Sinkhorn DivergenceDrifting Models

    Department of Computer Science, Vanderbilt University · Department of Computer Science, University of California, Davis · Department of Computer Science, Purdue University

  17. EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering

    Mar 12, 2026Nicolas Deutschmann, Constance Ferragu, Jonathan D. Ziegler +2Protein DesignSequence Modeling

    Cradle

  18. COT-FM: Cluster-wise Optimal Transport Flow Matching

    Mar 11, 2026Chiensheng Chiang, Kuan-Hsun Tu, Jia-Wei Liao +2Flow MatchingGenerative Modeling

    National Taiwan University

  19. Riemannian MeanFlow for One-Step Generation on Manifolds

    Mar 11, 2026Zichen Zhong, Haoliang Sun, Yukun Zhao +2Generative ModelingFlow-Based Generative Modeling

    School of Software, Shandong University, Jinan, China

  20. UHD Image Deblurring via Autoregressive Flow with Ill-conditioned Constraints

    Mar 11, 2026Yucheng Xin, Dawei Zhao, Xiang Chen +6Image DeblurringFlow-Based Generative Modeling

    Shandong Normal University · Qilu University of Technology · Nanjing University of Science and Technology +2

  21. Graph-GRPO: Training Graph Flow Models with Reinforcement Learning

    Mar 11, 2026Baoheng Zhu, Deyu Bo, Delvin Ce Zhang +1Graph GenerationFlow-Based Generative Modeling

    Beijing University of Posts and Telecommunications · National University of Singapore · University of Sheffield +1

  22. From Flow to One Step: Real-Time Multi-Modal Trajectory Policies via Implicit Maximum Likelihood Estimation-based Distribution Distillation

    Mar 10, 2026Ju Dong, Liding Zhang, Lei Zhang +7Maximum Marginal Likelihood EstimationRobot Imitation Learning

    TAMS (Technical Aspects of Multimodal Systems), Department of Informatics, University of Hamburg, Hamburg, Germany. · Technical University of Munich, Germany. · Agile Robots SE, Munich, Germany.

  23. The Coupling Within: Flow Matching via Distilled Normalizing Flows

    Mar 9, 2026David Berthelot, Tianrong Chen, Jiatao Gu +6Flow-Based Generative ModelingFlow Matching

  24. Statistical Inference via Generative Models: Flow Matching and Causal Inference

    Mar 9, 2026Shinto EguchiCausal InferenceFlow Matching

  25. Foley-Flow: Coordinated Video-to-Audio Generation with Masked Audio-Visual Alignment and Dynamic Conditional Flows

    Mar 9, 2026Shentong Mo, Yibing SongAudio-Video GenerationAudio-Visual Synchronization

    CMU / MBZUAI · DAMO Academy, Alibaba Group · Hupan Laboratory

  26. Self-Supervised Flow Matching for Scalable Multi-Modal Synthesis

    Mar 6, 2026Hila Chefer, Patrick Esser, Dominik Lorenz +5Flow-Based Generative ModelingFlow Matching

    Black Forest Labs · MIT

  27. Training Flow Matching: The Role of Weighting and Parameterization

    Mar 6, 2026Anne Gagneux, Ségolène Martin, Rémi Gribonval +1Flow MatchingAdaptive Loss Weighting

    ENS de Lyon, CNRS, Universit´e Claude Bernard Lyon 1, Inria, LIP, UMR 5668, France · Technische Universität Berlin, Germany · Inria, ENS de Lyon, CNRS, Universit´e Claude Bernard Lyon 1, LIP, UMR 5668, France

  28. LATO: 3D Mesh Flow Matching with Structured TOpology Preserving LAtents

    Mar 6, 2026Tianhao Zhao, Youjia Zhang, Hang Long +73D Mesh Generation3D Representation Learning

    Huazhong University of Science and Technology · Peking University · Independent Researcher +1

  29. Reflective Flow Sampling Enhancement

    Mar 6, 2026Zikai Zhou, Muyao Wang, Shitong Shao +4T2I Diffusion ModelsFlow-Based Generative Modeling

    The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China. · The University of Tokyo, Japan. · Microsoft, Beijing. +1

  30. Offline Materials Optimization with CliqueFlowmer

    Mar 6, 2026Jakub Grudzien Kuba, Benjamin Kurt Miller, Sergey Levine +1Materials DiscoveryComputational Materials Science

    BAIR, UC Berkeley, Berkeley, California, USA · FAIR, Meta, San Francisco, California, USA