Flow Matching

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Overview

Flow matching learns a velocity field that moves samples from a simple source, often Gaussian noise, toward a target data distribution. Conditional flow matching trains the field on paths between source and data samples, while optimal-transport couplings and rectified paths aim to make those trajectories easier to learn and integrate with an ordinary differential equation solver. Extensions handle discrete data, curved manifolds and symmetries, physical constraints, and applications from image and speech generation to robotics, scientific forecasting, and inverse problems. A central challenge is getting high fidelity and diverse, reliable samples with few solver steps; theory on convergence and stability is advancing, but the best paths, source distributions, and schedules depend on the task.

Latest papers

CardsList

663 papers123 papers in the last four weeks, up 68% on the four weeks before. 0.7% of all new papers.

  1. Mask2Flow-TSE: Two-Stage Target Speaker Extraction with Masking and Flow Matching

    Mar 13, 2026Junwon Moon, Seungbeom Kim, Hansol Park +4Target Speaker ExtractionFlow Matching

    Sungkyunkwan University · University of Seoul

  2. Self-Flow-Matching assisted Full Waveform Inversion

    Mar 13, 2026Xinquan Huang, Paris PerdikarisInverse ProblemsPhysics-Informed Generative Modeling

    University of Pennsylvania

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

    Mar 12, 2026Pengwei SunFlow MatchingFlow-Based Generative Modeling

    Stanford University

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

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

    Cradle

  5. The Quadratic Geometry of Flow Matching: Semantic Granularity Alignment for Text-to-Image Synthesis

    Mar 11, 2026Zhinan Xiong, Shunqi YuanFlow MatchingT2I Generation

    Conservatoire National des Arts et Métiers, Paris, France · Sun Yat-sen University, Guangzhou, China

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

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

    National Taiwan University

  7. AlphaFlowTSE: One-Step Generative Target Speaker Extraction via Conditional AlphaFlow

    Mar 11, 2026Duojia Li, Shuhan Zhang, Zihan Qian +5Target Speaker ExtractionOne-Step Generative Modeling

    School of Electronic Science and Engineering, Xiamen University, Xiamen, China · Shenzhen Loop Area Institute, Shenzhen, China · School of Artificial Intelligence, The Chinese University of Hong Kong, Shenzhen, Shenzhen, China +3

  8. VeloEdit: Training-Free Consistent and Continuous Instruction-Based Image Editing via Velocity Field Decomposition

    Mar 11, 2026Zongqing Li, Zhihui Liu, Yujie Xie +3Training-Free Image EditingImage Editing

    Xiamen University · Truesight

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

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

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

    Mar 9, 2026Shinto EguchiCausal InferenceFlow Matching

  11. 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

  12. 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

  13. 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

  14. Balancing Fidelity, Utility, and Privacy in Synthetic Cardiac MRI Generation: A Comparative Study

    Mar 4, 2026Madhura Edirisooriya, Dasuni Kawya, Ishan Kumarasinghe +5Medical Image SynthesisSynthetic Data Augmentation

    University of Peradeniya, Sri Lanka · University of Maryland, College Park, USA · Tulane University School of Medicine, USA; Simula Research Laboratory, Norway +1

  15. Linearized Coupling Flow with Shortcut Constraints for One-Step Face Restoration

    Mar 4, 2026Xiaohui Sun, Hanlin WuImage RestorationFlow Matching

    School of Information Science and Technology, Beijing Foreign Studies University, Beijing 100089, China

  16. Preconditioned Flow Matching

    Mar 2, 2026Shadab Ahamed, Eshed Gal, Md Shahriar Rahim Siddiqui +3Flow MatchingFlow-Based Generative Modeling

    University of British Columbia, Vancouver, Canada · University of Cambridge, Cambridge, United Kingdom

  17. Flow Matching-enabled Test-Time Refinement for Unsupervised Cardiac MR Registration

    Mar 1, 2026Yunguan Fu, Wenjia Bai, Wen Yan +3Medical Image RegistrationDeformable Image Registration

    University College London · InstaDeep · Imperial College London

  18. GeodesicNVS: Probability Density Geodesic Flow Matching for Novel View Synthesis

    Mar 1, 2026Xuqin Wang, Tao Wu, Yanfeng Zhang +5Novel View SynthesisFlow Matching

    Huawei Hilbert Research Center (Dresden) · Technical University of Munich · Karlsruhe University of Applied Sciences

  19. AG-REPA: Causal Layer Selection for Representation Alignment in Audio Flow Matching

    Mar 1, 2026Pengfei Zhang, Tianxin Xie, Minghao Yang +1Flow-Based Generative ModelingFlow Matching

    AI Thrust, Information Hub, The Hong Kong University of Science and Technology (Guangzhou).

  20. RAFM: Retrieval-Augmented Flow Matching for Unpaired CBCT-to-CT Translation

    Feb 28, 2026Xianhao Zhou, Jianghao Wu, Lanfeng Zhong +4Medical Image SynthesisImage-to-Image Translation

    School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China · Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia · Shanghai Artificial Intelligence Laboratory, Shanghai, China

  21. Efficient Flow Matching for Sparse-View CT Reconstruction

    Feb 27, 2026Jiayang Shi, Lincen Yang, Zhong Li +3Flow MatchingSparse-View CT Reconstruction

    Centrum Wiskunde en Informatica · LIACS, Leiden University · Great Bay University +1

  22. Flow Matching is Adaptive to Manifold Structures

    Feb 25, 2026Shivam Kumar, Yixin Wang, Lizhen LinFlow MatchingGenerative Modeling

    Booth School of Business, University of Chicago · Department of Statistics, University of Michigan · Department of Mathematics, University of Maryland, College Park

  23. Entropy-Controlled Flow Matching

    Feb 25, 2026Chika MaduabuchiFlow MatchingFlow-Based Generative Modeling

    William & Mary, Williamsburg, VA, USA

  24. D-Flow SGLD: Source-Space Posterior Sampling for Scientific Inverse Problems with Flow Matching

    Feb 25, 2026Meet Hemant Parikh, Yaqin Chen, Jian-Xun WangPosterior SamplingBayesian Inverse Problems

    Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, USA · Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, USA

  25. Laplacian Multi-scale Flow Matching for Generative Modeling

    Feb 23, 2026Zelin Zhao, Petr Molodyk, Haotian Xue +1Mixture-of-TransformersGenerative Modeling

    Georgia Institute of Technology Atlanta, GA 30332, USA

  26. AdsorbFlow: energy-conditioned flow matching enables fast and realistic adsorbate placement

    Feb 22, 2026Jiangjie Qiu, Wentao Li, Honghao Chen +2Flow-Based Generative ModelingMaterials Science

    Beijing Key Laboratory of Artificial Intelligence for Advanced Chemical Engineering Materials, Department of Chemical Engineering, Tsinghua University, Beijing, China.

  27. Flow Matching with Injected Noise for Offline-to-Online Reinforcement Learning

    Feb 20, 2026Yongjae Shin, Jongseong Chae, Jongeui Park +1Offline-To-Online RLSample-Efficient RL

    KAIST

  28. Balancing Symmetry and Efficiency in Graph Flow Matching

    Feb 20, 2026Benjamin Honoré, Alba Carballo-Castro, Yiming Qin +1Generative ModelingEquivariant GNNs

    LTS4, EPFL, Lausanne, Switzerland

  29. 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

  30. Variational Grey-Box Dynamics Matching

    Feb 19, 2026Gurjeet Sangra Singh, Frantzeska Lavda, Giangiacomo Mercatali +1Physics-Informed Generative ModelingSystem Identification