Generative Flows papers, 2023–2026

Key findings

• Generative Flows went from 73 papers in 2023 to 139 in 2026, roughly 1.9x in three years.
• NeurIPS publishes the most Generative Flows work: 130 papers from 2023 to 2026, 30% of the four-venue total.
• The fastest-growing overlap is with Applications · chemistry physics and earth sciences: papers tagged with both rose from 1 in 2023 to 5 in 2026.
• Among the 5 topics under Probabilistic and Bayesian, it ranks #3 by 2026 paper count; the fastest grower in the group, Gaussian Processes, is up 2.2x versus 1.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Exact Recovery of Lipschitz Orthogonal Coordinate Transformations via Constrained Normalizing Flows
• ICML 2026Learning-to-Optimize via Deep Unfolded Flows
• ICLR 2026Frozen Priors, Fluid Forecasts: Prequential Uncertainty for Low-Data Deployment with Pretrained Generative Models
• CVPR 2026AnchorFlow Training-Free 3D Editing via Latent Anchor-Aligned Flows
• NeurIPS 2025Amortized Sampling with Transferable Normalizing Flows
• ICML 2025Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions
• ICLR 2025Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks
• CVPR 2025DiverseFlow: Sample-Efficient Diverse Mode Coverage in Flows
• NeurIPS 2024Learning Distributions on Manifolds with Free-Form Flows
• ICML 2024A Computational Framework for Solving Wasserstein Lagrangian Flows
• ICLR 2024Fast and unified path gradient estimators for normalizing flows
• CVPR 2024Distributionally Generative Augmentation for Fair Facial Attribute Classification
• NeurIPS 2023Canonical normalizing flows for manifold learning
• ICML 2023MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows
• ICLR 2023AE-FLOW: Autoencoders with Normalizing Flows for Medical Images Anomaly Detection
• CVPR 2023Delving Into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling
• NeurIPS 2026From Baselines to Transport Geodesics: Axiomatic Attribution via Optimal Generative Flows
• ICML 2026Hyperbolic RQ-VAE enhanced Generative Recommendation with Differential-Length Codebook Strategy
• ICLR 2026JAPAN: Joint Adaptive Prediction Areas with Normalising Flow
• CVPR 2026BUSSARD Normalizing Flows for Bijective Universal Scene-Specific Anomalous Relationship Detection

All Generative Flows papers

130 papers, page 2 of 3

51. NeurIPS 2025Balanced Conic Rectified Flow
52. NeurIPS 2025Beyond Scores: Proximal Diffusion Models
53. NeurIPS 2025CDFlow: Building Invertible Layers with Circulant and Diagonal Matrices
54. NeurIPS 2025Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models
55. NeurIPS 2025Counterfactual Identifiability via Dynamic Optimal Transport
56. NeurIPS 2025DiCoFlex: Model-Agnostic Diverse Counterfactuals with Flexible Control
57. NeurIPS 2025Edit Flows: Variable Length Discrete Flow Matching with Sequence-Level Edit Operations
58. NeurIPS 2025Enhancing Consistency of Flow-Based Image Editing through Kalman Control
59. NeurIPS 2025Finding separatrices of dynamical flows with Deep Koopman Eigenfunctions
60. NeurIPS 2025Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows
61. NeurIPS 2025FLOWING: Implicit Neural Flows for Structure-Preserving Morphing
62. NeurIPS 2025From Information to Generative Exponent: Learning Rate Induces Phase Transitions in SGD
63. NeurIPS 2025Generative Distribution Embeddings
64. NeurIPS 2025Gradient Variance Reveals Failure Modes in Flow-Based Generative Models
65. NeurIPS 2025Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points
66. NeurIPS 2025Learning to Integrate Diffusion ODEs by Averaging the Derivatives
67. NeurIPS 2025MANGO: Multimodal Attention-based Normalizing Flow Approach to Fusion Learning
68. NeurIPS 2025Mean Flows for One-step Generative Modeling
69. NeurIPS 2025Missing Data Imputation by Reducing Mutual Information with Rectified Flows
70. NeurIPS 2025Multitask Learning with Stochastic Interpolants
71. NeurIPS 2025Multivariate Latent Recalibration for Conditional Normalizing Flows
72. NeurIPS 2025Normalizing Flows are Capable Models for Continuous Control
73. NeurIPS 2025Partial Information Decomposition via Normalizing Flows in Latent Gaussian Distributions
74. NeurIPS 2025Path Gradients after Flow Matching
75. NeurIPS 2025Riemannian Consistency Model
76. NeurIPS 2025SCoT: Unifying Consistency Models and Rectified Flows via Straight-Consistent Trajectories
77. NeurIPS 2025Seeds of Structure: Patch PCA Reveals Universal Compositional Cues in Diffusion Models
78. NeurIPS 2025Sequence Modeling with Spectral Mean Flows
79. NeurIPS 2025Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representations
80. NeurIPS 2025STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
81. NeurIPS 2025TARFVAE: Efficient One-Step Generative Time Series Forecasting via TARFLOW based VAE
82. NeurIPS 2025Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows
83. NeurIPS 2025When Models Don’t Collapse: On the Consistency of Iterative MLE
84. NeurIPS 2024A Generative Model of Symmetry Transformations
85. NeurIPS 2024ACES: Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
86. NeurIPS 2024AirSketch: Generative Motion to Sketch
87. NeurIPS 2024ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction
88. NeurIPS 2024Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
89. NeurIPS 2024CRAG - Comprehensive RAG Benchmark
90. NeurIPS 2024Dynamic Conditional Optimal Transport through Simulation-Free Flows
91. NeurIPS 2024Estimating the Hallucination Rate of Generative AI
92. NeurIPS 2024Exogenous Matching: Learning Good Proposals for Tractable Counterfactual Estimation
93. NeurIPS 2024FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification
94. NeurIPS 2024Fine-grained Control of Generative Data Augmentation in IoT Sensing
95. NeurIPS 2024Functional Gradient Flows for Constrained Sampling
96. NeurIPS 2024Generalized Eigenvalue Problems with Generative Priors
97. NeurIPS 2024Generative Forests
98. NeurIPS 2024Generative Fractional Diffusion Models
99. NeurIPS 2024Hamiltonian Score Matching and Generative Flows
100. NeurIPS 2024Improving the Training of Rectified Flows

FAQ

How many Generative Flows papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

429 in total: 73 in 2023, 98 in 2024, 119 in 2025, 139 in 2026.

How many Generative Flows papers are at NeurIPS 2026?

NeurIPS 2026 has 46 Generative Flows papers, versus 37 the year before.

How many Generative Flows papers are at ICLR 2026?

ICLR 2026 has 37 Generative Flows papers, versus 35 the year before.

How many Generative Flows papers are at ICML 2026?

ICML 2026 has 32 Generative Flows papers, versus 25 the year before.

How many Generative Flows papers are at CVPR 2026?

CVPR 2026 has 24 Generative Flows papers, versus 22 the year before.

Which conference publishes the most Generative Flows papers?

NeurIPS, with 130 papers from 2023 to 2026.