生成流论文趋势 2023–2026
Normalizing flows
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 429 篇被归入该主题的论文。
主要结论
- 生成流论文从 2023 年的 73 篇增长到 2026 年的 139 篇，三年间扩大到约 1.9 倍。
- NeurIPS 是发生成流论文最多的会议，2023–2026 年共 130 篇，占四个会议总量的 30%。
- 交叉方向里涨得最快的是应用 · chemistry physics and earth sciences：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 5 篇。
- 在「概率与贝叶斯」的 5 个主题里，它的 2026 年论文数排第 3；同组增长最快的高斯过程是 2.2 倍，生成流是 1.9 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 18 | 17 | 26 | 12 | 73 |
| 2024 | 29 | 18 | 27 | 24 | 98 |
| 2025 | 37 | 35 | 25 | 22 | 119 |
| 2026 | 46 | 37 | 32 | 24 | 139 |
代表论文
按年份和会议均匀挑选，方便快速看到每一届的样貌
- 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
全部生成流论文
共 29 篇，第 1 / 1 页
- NeurIPS 2024A Generative Model of Symmetry Transformations
- NeurIPS 2024ACES: Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
- NeurIPS 2024AirSketch: Generative Motion to Sketch
- NeurIPS 2024ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction
- NeurIPS 2024Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
- NeurIPS 2024CRAG - Comprehensive RAG Benchmark
- NeurIPS 2024Dynamic Conditional Optimal Transport through Simulation-Free Flows
- NeurIPS 2024Estimating the Hallucination Rate of Generative AI
- NeurIPS 2024Exogenous Matching: Learning Good Proposals for Tractable Counterfactual Estimation
- NeurIPS 2024FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification
- NeurIPS 2024Fine-grained Control of Generative Data Augmentation in IoT Sensing
- NeurIPS 2024Functional Gradient Flows for Constrained Sampling
- NeurIPS 2024Generalized Eigenvalue Problems with Generative Priors
- NeurIPS 2024Generative Forests
- NeurIPS 2024Generative Fractional Diffusion Models
- NeurIPS 2024Hamiltonian Score Matching and Generative Flows
- NeurIPS 2024Improving the Training of Rectified Flows
- NeurIPS 2024Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
- NeurIPS 2024Learning diffusion at lightspeed
- NeurIPS 2024Learning Diffusion Priors from Observations by Expectation Maximization
- NeurIPS 2024Learning Distributions on Manifolds with Free-Form Flows
- NeurIPS 2024Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows
- NeurIPS 2024Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
- NeurIPS 2024Mutual Information Estimation via Normalizing Flows
- NeurIPS 2024Navigating Chemical Space with Latent Flows
- NeurIPS 2024On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution
- NeurIPS 2024Optimal Flow Matching: Learning Straight Trajectories in Just One Step
- NeurIPS 2024Preferential Normalizing Flows
- NeurIPS 2024Transferable Boltzmann Generators
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查生成流在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "generative-flows"}
常见问题
- 2023–2026 年四大会议一共有多少篇生成流论文？
- 共 429 篇，按年份分别是 2023 年 73 篇、2024 年 98 篇、2025 年 119 篇、2026 年 139 篇。
- NeurIPS 2026 有多少篇生成流论文？
- NeurIPS 2026 有 46 篇生成流论文，上一届是 37 篇。
- ICLR 2026 有多少篇生成流论文？
- ICLR 2026 有 37 篇生成流论文，上一届是 35 篇。
- ICML 2026 有多少篇生成流论文？
- ICML 2026 有 32 篇生成流论文，上一届是 25 篇。
- CVPR 2026 有多少篇生成流论文？
- CVPR 2026 有 24 篇生成流论文，上一届是 22 篇。
- 哪个会议的生成流论文最多？
- NeurIPS，2023–2026 年共 130 篇。