深度学习 · generative models and autoencoders论文趋势 2023–2026
ICML/NeurIPS 深度学习方向：generative_models_and_autoencoders
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 4,314 篇被归入该主题的论文。
主要结论
- 深度学习 · generative models and autoencoders论文从 2023 年的 1,216 篇增长到 2026 年的 1,430 篇，三年间扩大到约 1.2 倍。
- NeurIPS 是发深度学习 · generative models and autoencoders论文最多的会议，2023–2026 年共 1,714 篇，占四个会议总量的 40%。
- 交叉方向里涨得最快的是图像生成：同时属于两个主题的论文从 2023 年的 35 篇增至 2026 年的 150 篇。
- 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 2；同组增长最快的扩散模型是 4.1 倍，深度学习 · generative models and autoencoders是 1.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 776 | 78 | 286 | 76 | 1,216 |
| 2024 | 349 | 174 | 139 | 106 | 768 |
| 2025 | 240 | 275 | 275 | 110 | 900 |
| 2026 | 349 | 303 | 604 | 174 | 1,430 |
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 2026A Critical $\beta$-Scale for Posterior Collapse in Dirichlet $\beta$-VAEs
- ICML 2026(1D) Ordered Tokens Enable Efficient Test-Time Search
- ICLR 2026``Noisier'’ Noise Contrastive Estimation is (Almost) Maximum Likelihood
- CVPR 2026Anchoring and Rescaling Attention for Semantically Coherent Inbetweening
- NeurIPS 2025Agnostic Learning under Targeted Poisoning: Optimal Rates and the Role of Randomness
- ICML 2025A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
- ICLR 2025A Watermark for Order-Agnostic Language Models
- CVPR 2025DUNE: Distilling a Universal Encoder from Heterogeneous 2D and 3D Teachers
- NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
- ICML 2024A Fixed-Point Approach for Causal Generative Modeling
- ICLR 2024$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
- CVPR 2024Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation
- NeurIPS 2023(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
- ICML 2023A Kernelized Stein Discrepancy for Biological Sequences
- ICLR 2023Arbitrary Virtual Try-on Network: Characteristics Representation and Trade-off between Body and Clothing
- CVPR 20233D GAN Inversion With Facial Symmetry Prior
- NeurIPS 2026Action-On-Item Preference Flow: A Shared Event Schema for Predictive and Generative Personalization
- ICML 2026$f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
- ICLR 2026Analyzing and Evaluating Unbiased Language Model Watermark
- CVPR 2026Bidirectional Normalizing Flow From Data to Noise and Back
全部深度学习 · generative models and autoencoders论文
共 900 篇，第 7 / 18 页
- ICLR 2025PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
- ICLR 2025PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
- ICLR 2025Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks
- ICLR 2025PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
- ICLR 2025PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
- ICLR 2025Probing the Latent Hierarchical Structure of Data via Diffusion Models
- ICLR 2025Progressive Compression with Universally Quantized Diffusion Models
- ICLR 2025Proteina: Scaling Flow-based Protein Structure Generative Models
- ICLR 2025ProtoSnap: Prototype Alignment For Cuneiform Signs
- ICLR 2025QA-Calibration of Language Model Confidence Scores
- ICLR 2025Quality Measures for Dynamic Graph Generative Models
- ICLR 2025Rapid Selection and Ordering of In-Context Demonstrations via Prompt Embedding Clustering
- ICLR 2025RB-Modulation: Training-Free Stylization using Reference-Based Modulation
- ICLR 2025Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow
- ICLR 2025ReGen: Generative Robot Simulation via Inverse Design
- ICLR 2025Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds
- ICLR 2025RelitLRM: Generative Relightable Radiance for Large Reconstruction Models
- ICLR 2025Representative Guidance: Diffusion Model Sampling with Coherence
- ICLR 2025Residual Stream Analysis with Multi-Layer SAEs
- ICLR 2025Restructuring Vector Quantization with the Rotation Trick
- ICLR 2025Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
- ICLR 2025Rethinking Artistic Copyright Infringements In the Era Of Text-to-Image Generative Models
- ICLR 2025Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
- ICLR 2025Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words
- ICLR 2025Rethinking Visual Counterfactual Explanations Through Region Constraint
- ICLR 2025Risk-Sensitive Diffusion: Robustly Optimizing Diffusion Models with Noisy Samples
- ICLR 2025Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport
- ICLR 2025RouteLLM: Learning to Route LLMs from Preference Data
- ICLR 2025Sample then Identify: A General Framework for Risk Control and Assessment in Multimodal Large Language Models
- ICLR 2025Scaling and evaluating sparse autoencoders
- ICLR 2025Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models
- ICLR 2025Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
- ICLR 2025Semantic Image Inversion and Editing using Rectified Stochastic Differential Equations
- ICLR 2025Shallow diffusion networks provably learn hidden low-dimensional structure
- ICLR 2025Simple ReFlow: Improved Techniques for Fast Flow Models
- ICLR 2025Simplifying, Stabilizing and Scaling Continuous-time Consistency Models
- ICLR 2025Sparse Autoencoders Do Not Find Canonical Units of Analysis
- ICLR 2025Sparse autoencoders reveal selective remapping of visual concepts during adaptation
- ICLR 2025Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models
- ICLR 2025Stiefel Flow Matching for Moment-Constrained Structure Elucidation
- ICLR 2025Streamlining Redundant Layers to Compress Large Language Models
- ICLR 2025SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency
- ICLR 2025Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
- ICLR 2025Sylber: Syllabic Embedding Representation of Speech from Raw Audio
- ICLR 2025SyllableLM: Learning Coarse Semantic Units for Speech Language Models
- ICLR 2025SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups
- ICLR 2025Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
- ICLR 2025T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching
- ICLR 2025TabWak: A Watermark for Tabular Diffusion Models
- ICLR 2025Text-to-Image Rectified Flow as Plug-and-Play Priors
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 查深度学习 · generative models and autoencoders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": "dl-generative-models-and-autoencoders"}
常见问题
- 2023–2026 年四大会议一共有多少篇深度学习 · generative models and autoencoders论文？
- 共 4,314 篇，按年份分别是 2023 年 1,216 篇、2024 年 768 篇、2025 年 900 篇、2026 年 1,430 篇。
- NeurIPS 2026 有多少篇深度学习 · generative models and autoencoders论文？
- NeurIPS 2026 有 349 篇深度学习 · generative models and autoencoders论文，上一届是 240 篇。
- ICLR 2026 有多少篇深度学习 · generative models and autoencoders论文？
- ICLR 2026 有 303 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。
- ICML 2026 有多少篇深度学习 · generative models and autoencoders论文？
- ICML 2026 有 604 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。
- CVPR 2026 有多少篇深度学习 · generative models and autoencoders论文？
- CVPR 2026 有 174 篇深度学习 · generative models and autoencoders论文，上一届是 110 篇。
- 哪个会议的深度学习 · generative models and autoencoders论文最多？
- NeurIPS，2023–2026 年共 1,714 篇。