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

900 papers, page 5 of 18

201. ICLR 2025Flow matching achieves almost minimax optimal convergence
202. ICLR 2025Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens
203. ICLR 2025Forte : Finding Outliers with Representation Typicality Estimation
204. ICLR 2025Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models
205. ICLR 2025From Search to Sampling: Generative Models for Robust Algorithmic Recourse
206. ICLR 2025Fugatto 1: Foundational Generative Audio Transformer Opus 1
207. ICLR 2025GANDALF: Generative AttentioN based Data Augmentation and predictive modeLing Framework for personalized cancer treatment
208. ICLR 2025Generalization and Distributed Learning of GFlowNets
209. ICLR 2025Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis
210. ICLR 2025Generalization through variance: how noise shapes inductive biases in diffusion models
211. ICLR 2025Generating Graphs via Spectral Diffusion
212. ICLR 2025Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
213. ICLR 2025Generative Classifiers Avoid Shortcut Solutions
214. ICLR 2025Generative Inbetweening: Adapting Image-to-Video Models for Keyframe Interpolation
215. ICLR 2025Generative Monoculture in Large Language Models
216. ICLR 2025Generative Representational Instruction Tuning
217. ICLR 2025Generative Verifiers: Reward Modeling as Next-Token Prediction
218. ICLR 2025Generator Matching: Generative modeling with arbitrary Markov processes
219. ICLR 2025GenSE: Generative Speech Enhancement via Language Models using Hierarchical Modeling
220. ICLR 2025GenVP: Generating Visual Puzzles with Contrastive Hierarchical VAEs
221. ICLR 2025GenXD: Generating Any 3D and 4D Scenes
222. ICLR 2025Geometry of Lightning Self-Attention: Identifiability and Dimension
223. ICLR 2025Glauber Generative Model: Discrete Diffusion Models via Binary Classification
224. ICLR 2025Global Well-posedness and Convergence Analysis of Score-based Generative Models via Sharp Lipschitz Estimates
225. ICLR 2025GMValuator: Similarity-based Data Valuation for Generative Models
226. ICLR 2025GOFA: A Generative One-For-All Model for Joint Graph Language Modeling
227. ICLR 2025GoodDrag: Towards Good Practices for Drag Editing with Diffusion Models
228. ICLR 2025GrabS: Generative Embodied Agent for 3D Object Segmentation without Scene Supervision
229. ICLR 2025GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement
230. ICLR 2025HaDeMiF: Hallucination Detection and Mitigation in Large Language Models
231. ICLR 2025Halton Scheduler for Masked Generative Image Transformer
232. ICLR 2025HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models
233. ICLR 2025Heavy-Tailed Diffusion Models
234. ICLR 2025Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models
235. ICLR 2025HexGen-2: Disaggregated Generative Inference of LLMs in Heterogeneous Environment
236. ICLR 2025HGM³: Hierarchical Generative Masked Motion Modeling with Hard Token Mining
237. ICLR 2025Hierarchical Autoregressive Transformers: Combining Byte- and Word-Level Processing for Robust, Adaptable Language Models
238. ICLR 2025High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders
239. ICLR 2025High-Quality Joint Image and Video Tokenization with Causal VAE
240. ICLR 2025High-quality Text-to-3D Character Generation with SparseCubes and Sparse Transformers.
241. ICLR 2025Holistically Evaluating the Environmental Impact of Creating Language Models
242. ICLR 2025How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
243. ICLR 2025How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning
244. ICLR 2025Hybrid Regularization Improves Diffusion-based Inverse Problem Solving
245. ICLR 2025IgGM: A Generative Model for Functional Antibody and Nanobody Design
246. ICLR 2025Improved Convergence Rate for Diffusion Probabilistic Models
247. ICLR 2025Improved Diffusion-based Generative Model with Better Adversarial Robustness
248. ICLR 2025Improved Training Technique for Latent Consistency Models
249. ICLR 2025Improving Equivariant Networks with Probabilistic Symmetry Breaking
250. ICLR 2025Improving Neural Optimal Transport via Displacement Interpolation

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.