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NeurIPS 2026SpotlightNanjing University of Science anNanjingFlow matching

Toward Semantically-Consistent Tuning-Free Customization for Rectified Flow Transformers

Jian Jin, Kai Zhang, Zhenyong Fu, Jian Yang

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ShenzhenFlow matching

Geometry-Aware Flow Matching for Sparse-View 3D Gaussian Splatting

Abdullah Azeem, Ruisheng Wang, Qingquan Li, Abubakar Siddique

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U MinnesotaFlow matching

State Augmented Flows

Dwij Mehta, Arvind Renganathan, Vipin Kumar

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Institute of automation, ChineseInstitute of Neuroscience, ChineChinease Academy of ScienceCenter for Excellence in Brain SFlow matching

SQUEEZE: Preserving Homeomorphism and Smooth in Higher-Dimensional Flows

Wangzi Yao, Yue Sun, Rongmin Chen, Honglie Wang and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U PittsburghU Virginia, CharlottesvilleU Texas at DallasFlow matching

Flow-Guided Target-Space Alignment via Path Consistency

Ruizhi Yuan, Zeqiu Yu, Wei Gao, Wei Chen and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Nanjing University of AeronauticNanjing University of AeronauticCentral China NormalCarnegie MellonFlow matching

ControlFlow3D: Distilling Multi-View Knowledge into Latent Flow Matching for Point Cloud Upsampling

Yuang Liu, Zhi Zuo, Zhengkai Zhao, Lirui Zhang and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Shanghai JiaotongShanghai AI Laboratory; ShanghaiTsinghuaFlow matching

CuBic: Curvature-Driven Dynamic Inference Caching for Fast, High-Fidelity Flow Matching

Yuyang Chen, Linqian Zeng, Yijin Zhou, Hengjie Li and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026South China University of TechnoRIKENXiaomi CorporationXiaomiFlow matching

Inference-Time Self-Aligned Drifting for Few-Step Flow Matching

Shigui Li, JIAN XU, Wei Chen, Junmei Yang and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U FloridaFlow matching

Exact Recovery of Lipschitz Orthogonal Coordinate Transformations via Constrained Normalizing Flows

Isaac Manring, Kejun Huang

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Seoul Nationalseoul national universityFlow matching

FLINT: Coupling Proximal Initialization and Bounded Stochasticity for Flow-Matching Inverse Problems

Junseo Bang, daewon choi, Dong Ju Mun, Se Young Chun

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Duke University, DukeDukeFlow matching

Co-Evolving Interpolants and Flows via Path-Flow Alignment

Zeyu M Li, William X Chen, Xiang Cheng

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026FudanWestlakeLi AutoFlow matching

High-Fidelity Boltzmann Samplingvia Physical Prior Lifted Continuous GFlowNets

Xizhi Tian, Wenhao Deng, Haojia Hui, Hang Chen and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightBeihangZhejiangThe University of Hong KongTsinghuaXiamenFlow matching

GenRM-Flow: Generators are Process-aware Reward Models in Flow Matching

Siming Fu, Zheming Fu, Ruizhe He, Zeyue Xue and 6 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026TsinghuaFlow matching

AegisFlow: Training-free Non-myopic Path-safe Guided Flow Matching

Kunpeng Liu, Boshi Zhang, Keyou You

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026LinköpingUppsalaFlow matching

ESS-Flow: training-free guidance as Bayesian inference in source space

Adhithyan Kalaivanan, Zheng Zhao, Jens Sjölund, Fredrik Lindsten

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026TuftsFlow matching

Primal-Dual Flow Matching for Sample-Wise Constrained Generation

Zhengyan Huan, Peter Y. Lu, Shuchin Aeron

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Hebei University of TechnologyFlow matching

DN-Flow: Driver–Navigator Structured Flow Matching for Mixed-Type Tabular Data Generation

Guangzhao Chai, Jing Liu, Youxi Wu, Yan Li

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U CambridgeU GlasgowFlow matching

Compatible Likelihoods for Flow Matching on Manifolds

Lucas Ng, Georgios Batzolis, Mark Girolami

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Robert Bosch GmbHTechnical University of DenmarkBosch Center for AIKarlsruhe Institute of TechnologItalian Institute of Artificial Flow matching

Contact Geometry for Generative Models: An Unbalanced Optimal Transport Formulation

Andrea Testa, Søren Hauberg, Andras Kupcsik, Tamim Asfour and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Huawei Technologies Ltd.Huawei Technologies CanadaFlow matching

Coupled Guidance for Flow Matching

Mateo Clémente, Leo Brunswic, Yang, Amir Rasouli

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026East China NormalEast China nornal universityInstitute of Statistical MathemaFlow matching

Geometric Velocity Regularity for Flow Matching on Manifold-Concentrated Data

Shuntuo Xu, Zhou Yu, Kenji Fukumizu

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026INRIAU UtahFlow matching

DeFlowCritic: Dense Latent Reward Alignment for Text-to-Image Flow Matching Models

Zeeshan Khan, Xin Yu, Shizhe Chen, Cordelia Schmid

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U Texas at AustinFlow matching

SiliciclasticReservoirs: A Million-Reservoir Dataset and Flow-Matching Foundation Model for 3D Siliciclastic Reservoir Generation

Ilgar Baghishov, Elnara Rustamzade, Graeme Henkelman, John Foster and 1 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026U California, IrvineWilliam & MaryFlow matching

Temporal Pair Consistency for Flow Matching

Chika Maduabuchi, Jindong Wang

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Macau University of Science and Macau University of Science and Pengcheng LaboratoryInstitute of automation, ChineseSun Yat-senFlow matching

Bernoulli Flow Models: Self-Consistent Generative Modeling for Binary Data

Hao Mo, Liying Yang, Shumin Yao, Xinxing Yu and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Imperial College LondonFlow matching

Mamba Flow Matching Neural Processes: Linear-Time Inference for Irregularly Observed Spatial Fields

Cosmo Santoni, Giovanni Charles, Timothy James Hitge, Oliver Watson and 1 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026KTH Royal Institute of TechnologKTH Royal Institute of TechnologFlow matching

Robust Flow Matching under Target Corruption and Label Noise

Mert Can Kurucu, Erik Englesson, Hossein Azizpour

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026PurdueU California, Santa CruzUC Santa CruzFlow matching

Stable GFlowNets with Probabilistic Guarantees

Zengxiang Lei, Ananth Shreekumar, Jonathan Rosenthal, Ruoyu Song and 5 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Weizmann Institute of ScienceMeta FAIRMetaFlow matching

Space Group Conditional Flow Matching

Omri Puny, Yaron Lipman, Benjamin K Miller

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026HSEFlow matching

Escaping the Curse of Dimensionality in One‑Step Flow-Based Generative Models

Konstantin Yakovlev

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026CAIRO, THWSTechnical University of Applied Flow matching

Plug-and-Play ADMM for Inverse Problems with Flow Matching Denoiser

Dibyanshu Kumar, Magda Gregorova

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026KAISTKorea Advanced Institute of ScieFlow matching

Root-Selecting Fixed-Point Inversion for Rectified Flows via Trajectory Straightness

SelFix selects fixed-point solutions by trajectory straightness for rectified flow inversion, improving reconstruction and editing accuracy.

Semin Kim, Jihwan Yoon, Seunghoon Hong

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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lenient 5/5
medium 7/10
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NeurIPS 2026The Hong Kong University of ScieHKUST, Guangzhou NVIDIAHKUSTHong Kong University of Science Flow matching

LucidNFT: LR-Anchored Multi-Reward Preference Optimization for Flow-Based Real-World Super-Resolution

LucidNFT improves flow-based real-world super-resolution via LR-anchored multi-reward preference optimization that reduces hallucinations while preserving perceptual quality.

Song Fei, Tian Ye, Sixiang Chen, Zhaohu Xing and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Seoul NationalPurdueSeoul National University GooglFlow matching

Probabilistic Signature Inversion: Learning Conditional Distributions from Truncated Signatures

Truncated signature inversion is reframed as learning conditional path distributions via signature-conditioned flow matching, with derived Bayes error baselines and validated reconstruction on real data.

Junoh Kang, Kiseop Lee, Bohyung Han

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Shanghai JiaotongAcademy of Military ScienceHuawei Technologies Ltd.Shanghai Jiao TongFlow matching

Accelerating Rectified Flow Models via Trajectory-Aware Caching

TACache decomposes rectified flow velocity errors into magnitude and direction components to skip steps and reconstruct velocities without extra evaluations, achieving up to 4.14x faster image and 2.11x faster video generation.

Xiao Liu, Kai Liu, Naiyang Guan, Hongliang Lu and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Huawei CanadaU British ColumbiaThe University of British ColumbU CambridgeFlow matching

Preconditioned Flow Matching

Ill-conditioned intermediate covariances make flow matching regress low-variance directions slowly; preconditioning into isotropic space improves optimization and generation quality.

Shadab Ahamed, Eshed Gal, Md Shahriar Rahim Siddiqui, Simon Ghyselincks and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026William & MaryCollege of William and MaryFlow matching

VTV-FM: Flow Matching through Variational Terminal-Velocity Closure

VTV-FM enables second-order flow matching via a minimum-acceleration variational terminal-velocity closure for static data, improving transport geometry and generation quality.

Haoyang Jiang, Yuheng Li, Di Yang, Yanhai Xiong and 2 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026New YorkKAIST / CMUKorea Advanced Institute of ScieFlow matching

Better Source, Better Flow: Learning Condition-Dependent Source Distribution for Flow Matching

Condition-dependent source distributions for flow matching improve text-to-image generation via variance regularization and directional alignment, accelerating convergence up to 3x in FID.

Junwan Kim, Jiho Park, Seonghu Jeon, Seungryong Kim

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026UCLABlockImperial College LondonFlow matching

Improving Function Space Flow Matching with Kernel Optimal Transport

kFFM replaces arbitrary pairing in Functional Flow Matching with kernel optimal transport to improve infinite-dimensional generative modeling and outperforms baselines on time-series and PDE benchmarks.

Fred Xu, Thomas Markovich, Barbora Barancikova, Yizhou Sun

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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72%Highly rated
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NeurIPS 2026GenentechYaleFlow matching

When Riemann flows with Wasserstein: Generative Modeling of Probability Distributions on Manifolds

RWEFM generatively models meta-distributions on manifolds via Riemannian Wasserstein flow matching, yielding valid flows and efficient GPU-optimal transport approximations for non-Euclidean data.

Doron Haviv, Edward De Brouwer, Rishabh Anand, Rex Ying and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 8 of 20 reviewers recommend it
lenient 3/5
medium 4/10
strict 1/5
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