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

275 papers, page 5 of 6

201. ICLR 2025Quality Measures for Dynamic Graph Generative Models
202. ICLR 2025Rapid Selection and Ordering of In-Context Demonstrations via Prompt Embedding Clustering
203. ICLR 2025RB-Modulation: Training-Free Stylization using Reference-Based Modulation
204. ICLR 2025Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow
205. ICLR 2025ReGen: Generative Robot Simulation via Inverse Design
206. ICLR 2025Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds
207. ICLR 2025RelitLRM: Generative Relightable Radiance for Large Reconstruction Models
208. ICLR 2025Representative Guidance: Diffusion Model Sampling with Coherence
209. ICLR 2025Residual Stream Analysis with Multi-Layer SAEs
210. ICLR 2025Restructuring Vector Quantization with the Rotation Trick
211. ICLR 2025Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
212. ICLR 2025Rethinking Artistic Copyright Infringements In the Era Of Text-to-Image Generative Models
213. ICLR 2025Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
214. ICLR 2025Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words
215. ICLR 2025Rethinking Visual Counterfactual Explanations Through Region Constraint
216. ICLR 2025Risk-Sensitive Diffusion: Robustly Optimizing Diffusion Models with Noisy Samples
217. ICLR 2025Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport
218. ICLR 2025RouteLLM: Learning to Route LLMs from Preference Data
219. ICLR 2025Sample then Identify: A General Framework for Risk Control and Assessment in Multimodal Large Language Models
220. ICLR 2025Scaling and evaluating sparse autoencoders
221. ICLR 2025Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models
222. ICLR 2025Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
223. ICLR 2025Semantic Image Inversion and Editing using Rectified Stochastic Differential Equations
224. ICLR 2025Shallow diffusion networks provably learn hidden low-dimensional structure
225. ICLR 2025Simple ReFlow: Improved Techniques for Fast Flow Models
226. ICLR 2025Simplifying, Stabilizing and Scaling Continuous-time Consistency Models
227. ICLR 2025Sparse Autoencoders Do Not Find Canonical Units of Analysis
228. ICLR 2025Sparse autoencoders reveal selective remapping of visual concepts during adaptation
229. ICLR 2025Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models
230. ICLR 2025Stiefel Flow Matching for Moment-Constrained Structure Elucidation
231. ICLR 2025Streamlining Redundant Layers to Compress Large Language Models
232. ICLR 2025SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency
233. ICLR 2025Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
234. ICLR 2025Sylber: Syllabic Embedding Representation of Speech from Raw Audio
235. ICLR 2025SyllableLM: Learning Coarse Semantic Units for Speech Language Models
236. ICLR 2025SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups
237. ICLR 2025Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
238. ICLR 2025T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching
239. ICLR 2025TabWak: A Watermark for Tabular Diffusion Models
240. ICLR 2025Text-to-Image Rectified Flow as Plug-and-Play Priors
241. ICLR 2025TFG-Flow: Training-free Guidance in Multimodal Generative Flow
242. ICLR 2025The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise
243. ICLR 2025The Superposition of Diffusion Models Using the Itô Density Estimator
244. ICLR 2025Think while You Generate: Discrete Diffusion with Planned Denoising
245. ICLR 2025ThunderKittens: Simple, Fast, and $\textit{Adorable}$ Kernels
246. ICLR 2025TidalDecode: Fast and Accurate LLM Decoding with Position Persistent Sparse Attention
247. ICLR 2025TIGeR: Unifying Text-to-Image Generation and Retrieval with Large Multimodal Models
248. ICLR 2025TopoDiffusionNet: A Topology-aware Diffusion Model
249. ICLR 2025Topological Schrödinger Bridge Matching
250. ICLR 2025Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers

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.