Deep learning · generative models and autoencoders papers, 2023–2026

Key findings

• Deep learning · generative models and autoencoders went from 1,216 papers in 2023 to 1,430 in 2026, roughly 1.2x in three years.
• NeurIPS publishes the most Deep learning · generative models and autoencoders work: 1,714 papers from 2023 to 2026, 40% of the four-venue total.
• The fastest-growing overlap is with Image Generation: papers tagged with both rose from 35 in 2023 to 150 in 2026.
• Among the 11 topics under Deep Learning, it ranks #2 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 1.2x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Deep learning · generative models and autoencoders papers

349 papers, page 4 of 7

151. NeurIPS 2026Inferring how internal brain state shapes neural responses with state-dependent diffusion models
152. NeurIPS 2026Information-Geometric Forward Policy Training in GFlowNets
153. NeurIPS 2026Invariance and Body-Order Compose Additively: Minimax Rates on $\mathrm{SO}(3)^n$
154. NeurIPS 2026Is a Linear Probe Evidence of a Linear Representation?
155. NeurIPS 2026Jailbreak susceptibility prediction and mitigation via the behavioral geometry of models
156. NeurIPS 2026JaSpec-LID: Local Intrinsic Dimension Estimation via Jacobian Spectra of ODE-based Generative Models
157. NeurIPS 2026Kernel-Gradient Drifting Models
158. NeurIPS 2026Koopman Generative Operators for Efficient Probabilistic Time-Series Forecasting
159. NeurIPS 2026Latent Process Generator Matching
160. NeurIPS 2026LayoutBridge: Anisotropic Brownian Bridges for Public Indoor Floorplan Generation
161. NeurIPS 2026Learn from Your Mistakes: Self-Correcting Masked Diffusion Models
162. NeurIPS 2026Learn from your own latents and not from tokens: A sample-complexity theory
163. NeurIPS 2026Learning a Unified Cross-Model Semantic Dictionary via Gated Bottleneck Sparse Autoencoders
164. NeurIPS 2026Learning Distributions from Multiple Data Providers
165. NeurIPS 2026Learning Generative Dynamics for 3D Molecule Generation via Sequential Neuro-Symbolic Constraints
166. NeurIPS 2026Learning to Align Generative Appearance Priors for Fine-grained Image Retrieval
167. NeurIPS 2026Learning to Solve Generative ODEs Beyond the Linear Span
168. NeurIPS 2026Less is More: Fewer Tokens and Blocks Make AIGI Detection Faster and More Generalizable
169. NeurIPS 2026Likelihood-Free Generative Policy Optimization
170. NeurIPS 2026LLM-Auction: Generative Auction towards LLM-Native Advertising
171. NeurIPS 2026Localizing and Repairing Sparse-Prompt Failure in SAM Decoders via Box-to-Point Counterfactual
172. NeurIPS 2026Looking Through the Mirror: Minimax-Optimal Regularized Regrets in Online Learning and Bandits
173. NeurIPS 2026Looking Under the Streetlight: Evaluation in Generative Molecular Dynamics
174. NeurIPS 2026LoRAtorio: An intrinsic approach to LoRA Skill Composition
175. NeurIPS 2026Magnetic Resonance Unpaired Image Translation with Pseudometric Schrödinger Bridges
176. NeurIPS 2026Masked Generative Pretraining Improves Cross-Dataset Transfer in Pixel-Space Diffusion
177. NeurIPS 2026Matryoshka Transcoders and Hierarchy Misalignment: When SAE Absorption Protection Does Not Transfer
178. NeurIPS 2026Meta Inverse Prompting for Video Generative Models
179. NeurIPS 2026MIND: Monge Inception Distance for Generative Models Evaluation
180. NeurIPS 2026MIRAGE: Mobile Agents with Implicit Reasoning and Generative World Models
181. NeurIPS 2026MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series
182. NeurIPS 2026Mixed-Curvature Geometric Latent Diffusion Model for Graph Generation
183. NeurIPS 2026Model Collapse is a Singular Complexity Trajectory
184. NeurIPS 2026Model-Based Online Decision Making via Generative Trajectory Planning
185. NeurIPS 2026Module Specialization in Transformer Factual Recall under Correlated Fact Distributions
186. NeurIPS 2026MOSAIC: Scaling Long-Horizon Language Agents via Multi-Scale Adaptive Inference Control
187. NeurIPS 2026Multi-step Consistency Models: A Complete Error Theory and Optimal Step Selection
188. NeurIPS 2026Multilevel and Sequential Monte Carlo for Training-Free Diffusion Guidance
189. NeurIPS 2026NAGO: Noise-Aware Generative Operator via Flow Matching
190. NeurIPS 2026Nahual: A Sequence Model for Language and Atoms
191. NeurIPS 2026Network Learning with Semi-relaxed Gromov-Wasserstein
192. NeurIPS 2026Neural Backward Filtering Forward Guiding
193. NeurIPS 2026Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction
194. NeurIPS 2026Neural Galerkin Normalizing Flows for Bayesian Inference of Diffusions with Inaccessible Boundaries
195. NeurIPS 2026Neuromodulated Constrained Autoencoders for Context-Dependent Manifold Learning
196. NeurIPS 2026NIV: Neural Axis Variations for Variable Font Generation
197. NeurIPS 2026No Model Required: Text Entropy Rate Filtering Prevents Iterative Fine-Tuning Collapse
198. NeurIPS 2026Noise-Started One-Step Image Super-Resolution via LR-Conditioned SplitMeanFlow and GAN Refinement
199. NeurIPS 2026Noisy2Latent: Nonparametric Deconvolution and Denoising via Maximum Mean Discrepancy
200. NeurIPS 2026Non-Expanding Gated Continued Fraction Architecture for Feedforward Layers in Language Models

FAQ

How many Deep learning · generative models and autoencoders papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

4,314 in total: 1,216 in 2023, 768 in 2024, 900 in 2025, 1,430 in 2026.

How many Deep learning · generative models and autoencoders papers are at NeurIPS 2026?

NeurIPS 2026 has 349 Deep learning · generative models and autoencoders papers, versus 240 the year before.

How many Deep learning · generative models and autoencoders papers are at ICLR 2026?

ICLR 2026 has 303 Deep learning · generative models and autoencoders papers, versus 275 the year before.

How many Deep learning · generative models and autoencoders papers are at ICML 2026?

ICML 2026 has 604 Deep learning · generative models and autoencoders papers, versus 275 the year before.

How many Deep learning · generative models and autoencoders papers are at CVPR 2026?

CVPR 2026 has 174 Deep learning · generative models and autoencoders papers, versus 110 the year before.

Which conference publishes the most Deep learning · generative models and autoencoders papers?

NeurIPS, with 1,714 papers from 2023 to 2026.