深度学习 · generative models and autoencoders论文趋势 2023–2026

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。

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 4,314 篇，第 24 / 87 页

1151. NeurIPS 2026Discrete Diffusion Models Exploit Asymmetry to Solve Lookahead Planning Tasks
1152. NeurIPS 2026Discrete Diffusion Playground: A 2D Benchmark for Discrete Generative Models
1153. NeurIPS 2026Discrete Flow Matching: Convergence Guarantees Under Minimal Assumptions
1154. NeurIPS 2026Discriminative Score Function: Turning Pretrained Models into Functional Generative Priors
1155. NeurIPS 2026Disentanglement as Identifiable Pushforward Factorisation
1156. NeurIPS 2026Displacement Geometry Captures Platonic Shared Reality Across Models and Modalities
1157. NeurIPS 2026Do Sparse Autoencoders Learn Meaningful Concept Hierarchies?
1158. NeurIPS 2026dRAE: Representation Autoencoder with Hyper-Spherical Codes
1159. NeurIPS 2026DrPO: Drifting Preference Optimization for One-Step Generative Models
1160. NeurIPS 2026Dual-Contrastive Sparse Autoencoders Reveal Features of Musical Interpretation
1161. NeurIPS 2026DualDrift: Combining Forward and Reverse Drifts for One-Step Generative Modeling
1162. NeurIPS 2026DySurface: Consistent 4D Surface Reconstruction via Bridging Explicit Gaussians and Implicit Functions
1163. NeurIPS 2026E-GEO: A Testbed for Generative Engine Optimization in E-Commerce
1164. NeurIPS 2026Efficient Off-Policy RL for Video Generation via Forward-Consistent Reward Matching
1165. NeurIPS 2026Efficient Reasoning via Constrained Optimization in Latent Space
1166. NeurIPS 2026Emergence of Distortions in High-Dimensional Guided Diffusion Models
1167. NeurIPS 2026Emergence, Retention and Mitigation of Ill-conditioning due to Basis Lifting in KANs
1168. NeurIPS 2026Empowering Masked Diffusion Models to Self-Correct with Leave-One-Out Transformers
1169. NeurIPS 2026Enabling Denoising Score Matching Type Training for Manifold Diffusion Model via Momentum and Splitting
1170. NeurIPS 2026End-to-End Identifiable and Consistent Recurrent Switching Dynamical Systems
1171. NeurIPS 2026Energy-Tweedie: Score meets Score, Energy meets Energy
1172. NeurIPS 2026Enhanced convergence guarantees of score-based generative models in $\mathcal{W}_2$-distance beyond log-concavity
1173. NeurIPS 2026Entropy Distribution as a Fingerprint for Hallucinations in Generative Models
1174. NeurIPS 2026Escaping the Curse of Dimensionality in One‑Step Flow-Based Generative Models
1175. NeurIPS 2026Every Measurement, Every Direction, All at Once: Multimodal Flow Matching for Molecules and Spectra
1176. NeurIPS 2026Exact Channel Decoupling via Joint Diagonalization and Uniform Splicing for Diffusion Transformer Quantization
1177. NeurIPS 2026Expanding Flow Maps
1178. NeurIPS 2026Expected Batch Optimal Transport Plans and Consequences for Flow Matching
1179. NeurIPS 2026FaceProbe: Recovering HDR Environment Map via Masked Diffusion and Physical Preference
1180. NeurIPS 2026Factored Generative Models through Mechanism Diversity
1181. NeurIPS 2026Fast and Accurate Probing of In-Training LLMs' Downstream Performances
1182. NeurIPS 2026Fast and Consistent Structure Learning in Graphical Models via Approximate Cross-Validation
1183. NeurIPS 2026FAST-Brain: A Flow-Aligned Spatio-Temporal Surrogate Brain Model
1184. NeurIPS 2026Ferrogen: Generative Pipeline for Guided Search of Novel Ferroelectric Material for Logic and Memory
1185. NeurIPS 2026Few-Step Cofolding with All-Atom Flow Maps
1186. NeurIPS 2026Fine-Tuning Improves Information Conveyance in Language Models
1187. NeurIPS 2026Fix the Structural Bottleneck: Context Compression via Explicit Information Transmission
1188. NeurIPS 2026Fixed-Point Masked Generative Modeling
1189. NeurIPS 2026Flowette: Flow Matching with Graphette Priors for Graph Generation
1190. NeurIPS 2026FluxLite: Inference-Time Proposal Control for Discrete Diffusion Models
1191. NeurIPS 2026FoMo: Forking Moment in Generative Trajectory as a Perceptual Distance
1192. NeurIPS 2026Frank-LoRA: Federated Rank-Aware LoRA for Fine-Tuning Large Models
1193. NeurIPS 2026From Baselines to Transport Geodesics: Axiomatic Attribution via Optimal Generative Flows
1194. NeurIPS 2026From Jumps to Signatures: a Generative Method for Temporal Point Processes
1195. NeurIPS 2026From Static Geometry to Dynamical Singularity: Detecting Memorization in Diffusion Models via Score Evolution
1196. NeurIPS 2026Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering with Generative Optimization
1197. NeurIPS 2026Full-Sequence Masked Diffusion for Generative Recommendation
1198. NeurIPS 2026G2Fusion: Geometric-to-Generative Image Fusion via Registration-Restoration Evolution
1199. NeurIPS 2026GazeFlow: From Human Gaze Behavior to Generative Egocentric Gaze Prediction
1200. NeurIPS 2026GenEnv: Difficulty-Aligned Co-Evolution Between LLM Agents and Environment Simulators

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。