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 26 / 87 页

1251. NeurIPS 2026LLM-Auction: Generative Auction towards LLM-Native Advertising
1252. NeurIPS 2026Localizing and Repairing Sparse-Prompt Failure in SAM Decoders via Box-to-Point Counterfactual
1253. NeurIPS 2026Looking Through the Mirror: Minimax-Optimal Regularized Regrets in Online Learning and Bandits
1254. NeurIPS 2026Looking Under the Streetlight: Evaluation in Generative Molecular Dynamics
1255. NeurIPS 2026LoRAtorio: An intrinsic approach to LoRA Skill Composition
1256. NeurIPS 2026Magnetic Resonance Unpaired Image Translation with Pseudometric Schrödinger Bridges
1257. NeurIPS 2026Masked Generative Pretraining Improves Cross-Dataset Transfer in Pixel-Space Diffusion
1258. NeurIPS 2026Matryoshka Transcoders and Hierarchy Misalignment: When SAE Absorption Protection Does Not Transfer
1259. NeurIPS 2026Meta Inverse Prompting for Video Generative Models
1260. NeurIPS 2026MIND: Monge Inception Distance for Generative Models Evaluation
1261. NeurIPS 2026MIRAGE: Mobile Agents with Implicit Reasoning and Generative World Models
1262. NeurIPS 2026MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series
1263. NeurIPS 2026Mixed-Curvature Geometric Latent Diffusion Model for Graph Generation
1264. NeurIPS 2026Model Collapse is a Singular Complexity Trajectory
1265. NeurIPS 2026Model-Based Online Decision Making via Generative Trajectory Planning
1266. NeurIPS 2026Module Specialization in Transformer Factual Recall under Correlated Fact Distributions
1267. NeurIPS 2026MOSAIC: Scaling Long-Horizon Language Agents via Multi-Scale Adaptive Inference Control
1268. NeurIPS 2026Multi-step Consistency Models: A Complete Error Theory and Optimal Step Selection
1269. NeurIPS 2026Multilevel and Sequential Monte Carlo for Training-Free Diffusion Guidance
1270. NeurIPS 2026NAGO: Noise-Aware Generative Operator via Flow Matching
1271. NeurIPS 2026Nahual: A Sequence Model for Language and Atoms
1272. NeurIPS 2026Network Learning with Semi-relaxed Gromov-Wasserstein
1273. NeurIPS 2026Neural Backward Filtering Forward Guiding
1274. NeurIPS 2026Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction
1275. NeurIPS 2026Neural Galerkin Normalizing Flows for Bayesian Inference of Diffusions with Inaccessible Boundaries
1276. NeurIPS 2026Neuromodulated Constrained Autoencoders for Context-Dependent Manifold Learning
1277. NeurIPS 2026NIV: Neural Axis Variations for Variable Font Generation
1278. NeurIPS 2026No Model Required: Text Entropy Rate Filtering Prevents Iterative Fine-Tuning Collapse
1279. NeurIPS 2026Noise-Started One-Step Image Super-Resolution via LR-Conditioned SplitMeanFlow and GAN Refinement
1280. NeurIPS 2026Noisy2Latent: Nonparametric Deconvolution and Denoising via Maximum Mean Discrepancy
1281. NeurIPS 2026Non-Expanding Gated Continued Fraction Architecture for Feedforward Layers in Language Models
1282. NeurIPS 2026Nonparametric In-Context Learning under Growing Geometric Complexity: Minimax Optimality and Local Geometry-Adaptivity of Transformers
1283. NeurIPS 2026Normalizing Trajectory Models
1284. NeurIPS 2026Not Suppressing or Purifying: Backdoor Containment via Expert Quarantine and Shutdown in LLMs
1285. NeurIPS 2026Not Too Generative, Not Too Discriminative: The Human Alignment Sweet Spot
1286. NeurIPS 2026On approximation and estimation of Schrödinger potentials without the curse of dimensionality
1287. NeurIPS 2026On the Depth of Monotone ReLU Neural Networks and ICNNs
1288. NeurIPS 2026On the Selectivity of Generative Models in Structure-Based Drug Design
1289. NeurIPS 2026On the Sparsity-Storage-Accuracy Tradeoff in Parsimoniously Activated Dictionary Learning
1290. NeurIPS 2026On the Tightness and Computational Tractability of Higher-Dimensional Confidence Sequences
1291. NeurIPS 2026One-Shot Generative Flows: Existence and Obstructions
1292. NeurIPS 2026OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework
1293. NeurIPS 2026Optimistic Dual Averaging Unifies Modern Optimizers
1294. NeurIPS 2026Order-Optimal Sample Complexity for Distribution Learning via Flow Matching
1295. NeurIPS 2026Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering
1296. NeurIPS 2026PatchBench: Measuring Collateral Damage in Activation Patching
1297. NeurIPS 2026Patching Up Circuit Learning on Images
1298. NeurIPS 2026Path-independent Flow Matching for Multi-parameter Generative Dynamics
1299. NeurIPS 2026PEEK: One-Step Look-Ahead Exposure Bias Correction for Diffusion Sampling
1300. NeurIPS 2026Permutation-Invariant Spectral Learning via Dyson Diffusion

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。