Conditional Flow Matching

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Generative Flow Networks

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Conditional Flow Matching

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Hierarchical Flow Matching

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Velocity Field

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Vector Fields

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Path-independent Flow Matching for Multi-parameter Generative Dynamics
May 13, 2026Francisco Téllez, AmirHossein Zamani, Philippe Martin +5Conditional Flow Matching Vector Fields
Support-Conditioned Flow Matching Is Kernel Smoothing
May 13, 2026Daniel Matsui SmolaKernel Method Conditional Flow Matching
Do Heavy Tails Help Diffusion? On the Subtle Trade-off Between Initialization and Training
May 13, 2026Hamza Cherkaoui, Hélène Halconruy, Antonio OcelloLong-Tailed Distribution Discrete Diffusion Model
Ergodic Trajectory Design by Learned Pushforward Maps: Provable Coverage via Conditional Flow Matching
May 13, 2026Ehsan Aghazadeh, Masoud Malekzadeh, Ahmad Ghasemi +1Trajectory Optimization Finite-Sample Coverage Guarantees
Asymmetric Flow Models
May 13, 2026Hansheng Chen, Jan Ackermann, Minseo Kim +2Generative Flow Networks Optical Flow
Coreset-Induced Conditional Velocity Flow Matching
May 13, 2026Xiao Wang, Zihua She, Jianxi SuConditional Flow Matching Generative Models
Reinforced Collaboration in Multi-Agent Flow Networks
May 13, 2026Zheng Wang, Yuang Liu, Yangkai DingCollaboration Generative Flow Networks
Discrete MeanFlow: One-Step Generation via Conditional Transition Kernels
May 12, 2026Fairoz Nower Khan, Nabuat Zaman Nahim, Md Sajid Ahmed +2Generative Flow Networks Few-Step Generation
Constraint-Aware Flow Matching: Decision Aligned End-to-End Training for Constrained Sampling
May 12, 2026Jacob K. Christopher, James E. Warner, Ferdinando FiorettoGenerative Models Hierarchical Flow Matching
Discrete Flow Matching for Offline-to-Online Reinforcement Learning
May 12, 2026Fairoz Nower Khan, Nabuat Zaman Nahim, Peizhong JuOffline Reinforcement Learning Flow-Based Policy
Morphologically Equivariant Flow Matching for Bimanual Mobile Manipulation
May 12, 2026Max Siebenborn, Daniel Ordoñez Apraez, Sophie Lueth +4Bimanual Manipulation Robotic Manipulation Policies
Expected Batch Optimal Transport Plans and Consequences for Flow Matching
May 12, 2026Samuel Boïté, Julie Delon, Kimia NadjahiOptimal Transport Batch Size
When Policy Entropy Constraint Fails: Preserving Diversity in Flow-based RLHF via Perceptual Entropy
May 12, 2026Xiaofeng Tan, Jun Liu, Bin-Bin Gao +5Diversity Reinforcement Learning From Human Feedback
Vector Scaffolding: Inter-Scale Orchestration for Differentiable Image Vectorization
May 12, 2026Jaerin Lee, Kanggeon Lee, Kyoung Mu LeeScalable Vector Graphic Multiscale
Sharpen Your Flow: Sharpness-Aware Sampling for Flow Matching
May 12, 2026Aditi Gupta, Soon Hoe Lim, Annan Yu +1Velocity Field Sharpness-Aware Minimization
LPDP: Inference-Time Reward Control for Variable-Length DNA Generation with Edit Flows
May 12, 2026Jeongchan Kim, Yunkyung Ko, Jong Chul YeMessenger Rna Generative Flow Networks
Language Modeling with Hyperspherical Flows
May 11, 2026Justin Deschenaux, Caglar GulcehreDiffusion Language Models Generative Flow Networks
Exact Fixed-Point Constraints in Neural-ODEs with Provable Universality
May 11, 2026Feliciano Giuseppe Pacifico, Duccio Fanelli, Lorenzo Buffoni +3Neural Ordinary Differential Equations Fixed-Point Iteration
VeloGauss: Learning Physically Consistent Gaussian Velocity Fields from Videos
May 11, 2026Nengbo Lu, Bin ZhaoVelocity Field 3D Gaussian Splatting
ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching
May 11, 2026Shuoheng Zhang, Yifu Yuan, Hongyao Tang +7Ground Reaction Forces Contact Forces
Follow the Mean: Reference-Guided Flow Matching
May 11, 2026Pedro M. P. Curvo, Maksim Zhdanov, Floor Eijkelboom +1Generative Flow Networks Neural Guidance
UFO: A Unified Flow-Oriented Framework for Robust Continual Graph Learning
May 11, 2026Danhui Zhang, Zhe Wang, Qing Qing +6Graph Representation Learning Efficient Continual Learning
Inverse Design for Conditional Distribution Matching
May 10, 2026Ori Meidler, Shaul Tolkovsky, Or ZukGenerative Inverse Design Conditional Distribution
Kinetic-Optimal Scheduling with Moment Correction for Metric-Induced Discrete Flow Matching in Zero-Shot Text-to-Speech
May 10, 2026Dong Yang, Yiyi Cai, Haoyu Zhang +2Zero-Shot Text-To-Speech Conditional Flow Matching
LagrangianSplats: Divergence-Free Transport of Gaussian Primitives for Fluid Reconstruction
May 10, 2026Ningxiao Tao, Baoquan Chen, Mengyu ChuVelocity Field Lagrangian Methods
dFlowGRPO: Rate-Aware Policy Optimization for Discrete Flow Models
May 10, 2026Zhengyan Wan, Yidong Ouyang, Panwen Hu +1Generative Flow Networks Flow-Based Policy
On Variance Reduction in Learning Mean Flows
May 10, 2026Juanwu Lu, Ziran WangGenerative Flow Networks Velocity Field
Discrete Flow Matching: Convergence Guarantees Under Minimal Assumptions
May 9, 2026Le-Tuyet-Nhi Pham, Giovanni Conforti, Zhenjie Ren +1Conditional Flow Matching Maximum Mean Discrepancy
Restoration-Aligned Generative Flow Models for Blind Motion Deblurring
May 9, 2026Insoo Kim, Jinwoo ShinMotion Blur Generative Flow Networks
Trajectory-Consistent Flow Matching for Robust Visuomotor Policy Learning
May 8, 2026Riad Ahmed, Sujosh Nag, Moniruzzaman Akash +2Visuomotor Policy Hierarchical Flow Matching
Recovering Physical Dynamics from Discrete Observations via Intrinsic Differential Consistency
May 8, 2026Yuxiang Luo, Andrew PerraultNeural Ordinary Differential Equations Velocity Field
Generalized Wasserstein Flow Matching: Transport Plans, Everywhere, All at Once
May 8, 2026Moritz Piening, Richard Duong, Gabriele SteidlVelocity Field Generative Models
Exploring and Exploiting Stability in Latent Flow Matching
May 8, 2026Rania Briq, Michael Kamp, Ohad Fried +2Generative Flow Networks Generative Models
Flow-OPD: On-Policy Distillation for Flow Matching Models
May 8, 2026Zhen Fang, Wenxuan Huang, Yu Zeng +8Hierarchical Flow Matching Video-Text Alignment
Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation
May 8, 2026Amin Karimi Monsefi, Dominic Culver, Nikhil Bhendawade +3Conditional Flow Matching Few-Step Generation
Scaling Categorical Flow Maps
May 8, 2026Oscar Davis, Anastasiia Filippova, Pierre Ablin +4Generative Flow Networks Flow Map
Flow Matching for Count Data
May 8, 2026Ganchao Wei, John PearsonGenerative Flow Networks Counting
Tessellations of Semi-Discrete Flow Matching
May 8, 2026Emile Pierret, Johannes Hertrich, Samuel Hurault +1Conditional Flow Matching Optimal Transport
Tools as Continuous Flow for Evolving Agentic Reasoning
May 8, 2026Tairan Huang, Siyu Shang, Qiang Chen +2Agentic Reasoning Agentic Tool Use
Generative Modeling with Flux Matching
May 8, 2026Peter Pao-Huang, Xiaojie Qiu, Stefano ErmonGenerative Models Score-Based Diffusion Model
Flow-Direct: Feedback-Efficient and Reusable Guidance for Flow Models via Non-Parametric Guidance Field
May 8, 2026Kim Yong Tan, Yueming Lyu, Ivor Tsang +1Generative Flow Networks Neural Guidance
Physics-Based Flow Matching for Full-Field Prediction of Silicon Photonic Devices
May 7, 2026Joseph Quaratiello, Anthony RizzoPhotonic Devices Conditional Flow Matching
Tyche: One Step Flow for Efficient Probabilistic Weather Forecasting
May 7, 2026Fan Xu, Yuan Gao, Kun Wang +4Generative Flow Networks Traffic
Conservative Flows: A New Paradigm of Generative Models
May 7, 2026Eshed Gal, Md Shahriar Rahim Siddiqui, Moshe Eliasof +1Generative Flow Networks Generative Models
A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models
May 7, 2026Aditya Ranganath, Mukesh SinghalScore-Based Diffusion Model Generative Models
Improved techniques for fine-tuning flow models via adjoint matching: a deterministic control pipeline
May 7, 2026Zhengyi Guo, Jiayuan Sheng, David D. Yao +1Generative Flow Networks Adjoint Matching
Efficient Serving for Dynamic Agent Workflows with Prediction-based KV-Cache Management
May 7, 2026Haoyu Zheng, Fangcheng Fu, Jia Wu +6Kv-Cache Blocks Agentic Workflows
Flow Matching with Arbitrary Auxiliary Paths
May 7, 2026Xin Peng, Ang GaoConditional Flow Matching
A Flow Matching Algorithm for Many-Shot Adaptation to Unseen Distributions
May 7, 2026Tyler Ingebrand, Ruihan Zhao, Kushagra Gupta +3Generative Models Parameter-Efficient Adaptation
P-Guide: Parameter-Efficient Prior Steering for Single-Pass CFG Inference
May 7, 2026Xin Peng, Ang GaoGenerative Priors Generative Flow Networks
Beyond Steering Vector: Flow-based Activation Steering for Inference-Time Intervention
May 7, 2026Zehao Jin, Ruixuan Deng, Junran Wang +2Activation Steering Steering
RepFlow: Representation Enhanced Flow Matching for Causal Effect Estimation
May 7, 2026Yifei Xie, Jian HuangCausal Inferences Selection Bias
SDFlow: Similarity-Driven Flow Matching for Time Series Generation
May 7, 2026Wei Li, Shibo Feng, Pengcheng Wu +3Generative Flow Networks Hierarchical Flow Matching
Spherical Flows for Sampling Categorical Data
May 7, 2026Jannis Chemseddine, Gregor Kornhardt, Gabriele SteidlGenerative Flow Networks Generative Models
Direct Product Flow Matching: Decoupling Radial and Angular Dynamics for Few-Shot Adaptation
May 6, 2026Hongxu Chen, Yanghao Wang, Bowei Zhu +6Few-Shot Learning Cross-Modal Alignment
FluxFlow: Conservative Flow-Matching for Astronomical Image Super-Resolution
May 5, 2026Shuhong Liu, Xining Ge, Ziteng Cui +8Phase-Folded Light Curves Conditional Flow Matching
Mixture Prototype Flow Matching for Open-Set Supervised Anomaly Detection
May 4, 2026Fuyun Wang, Yuanzhi Wang, Xu Guo +6Reconstruction-Based Anomaly Detection Anomaly Detection
Stable GFlowNets with Probabilistic Guarantees
May 3, 2026Zengxiang Lei, Ananth Shreekumar, Jonathan Rosenthal +6Generative Flow Networks Distributional Learning
Posterior Augmented Flow Matching
May 1, 2026George Stoica, Sayak Paul, Matthew Wallingford +6Hierarchical Flow Matching Collapse
Stable-GFlowNet: Toward Diverse and Robust LLM Red-Teaming via Contrastive Trajectory Balance
May 1, 2026Minchan Kwon, Sunghyun Baek, Minseo Kim +3Generative Flow Networks Large Language Model Safety

May 13, 2026 · cs.LGJ/K move · Enter open · S save

Path-independent Flow Matching for Multi-parameter Generative Dynamics

Francisco Téllez, AmirHossein Zamani, Philippe Martin, Shuang Ni+4

Université de Montréal, Mila · Concordia University, Mila · Concordia University · Royal Military College of Canada · Queen’s University, Mila

Flow Matching is a powerful framework for learning transport maps between probability distributions. Yet its standard single-parameter formulation is not designed to capture multi-parameter variations where the resulting transport should be path-independent. Path independence is crucial because it ensures that transformations depend only on the initial and target distributions, not on the specific path. In this work, we introduce Path-independent Flow Matching (PiFM), a method for learning vector fields whose induced flows yield path-independent transport between distributions. We show that PiFM generalizes Flow Matching to higher-dimensional parameter domains while enforcing structural conditions that ensure consistency of composed transformations. In addition, we show that, under suitable assumptions, PiFM approximates the Wasserstein barycenter, linking the framework to a notion of distributional interpolation. To enable practical training, we propose a tractable, simulation-free objective that regresses onto multi-parameter conditional probability paths. We showcase empirically that PiFM outperforms other approaches on both synthetic and real world data in interpolating path-independent trajectories and generating desired out of distribution samples.

Conditional Flow Matching Vector Fields Interpolation Probability

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