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 5 of 7

201. NeurIPS 2024MIDGArD: Modular Interpretable Diffusion over Graphs for Articulated Designs
202. NeurIPS 2024Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes
203. NeurIPS 2024MoGenTS: Motion Generation based on Spatial-Temporal Joint Modeling
204. NeurIPS 2024Molecule Design by Latent Prompt Transformer
205. NeurIPS 2024MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models
206. NeurIPS 2024MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders
207. NeurIPS 2024MotionCraft: Physics-Based Zero-Shot Video Generation
208. NeurIPS 2024MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
209. NeurIPS 2024Multimodal Large Language Models Make Text-to-Image Generative Models Align Better
210. NeurIPS 2024Multistep Distillation of Diffusion Models via Moment Matching
211. NeurIPS 2024MVGamba: Unify 3D Content Generation as State Space Sequence Modeling
212. NeurIPS 2024MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing
213. NeurIPS 2024MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views
214. NeurIPS 2024Nature-Inspired Local Propagation
215. NeurIPS 2024Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model
216. NeurIPS 2024Nearest Neighbor Speculative Decoding for LLM Generation and Attribution
217. NeurIPS 2024Neural Cover Selection for Image Steganography
218. NeurIPS 2024Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling
219. NeurIPS 2024Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses
220. NeurIPS 2024OmniTokenizer: A Joint Image-Video Tokenizer for Visual Generation
221. NeurIPS 2024On Divergence Measures for Training GFlowNets
222. NeurIPS 2024On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
223. NeurIPS 2024On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models
224. NeurIPS 2024On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)
225. NeurIPS 2024On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
226. NeurIPS 2024On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution
227. NeurIPS 2024On the Noise Robustness of In-Context Learning for Text Generation
228. NeurIPS 2024One-Shot Safety Alignment for Large Language Models via Optimal Dualization
229. NeurIPS 2024Optimal Flow Matching: Learning Straight Trajectories in Just One Step
230. NeurIPS 2024Optimal Multiclass U-Calibration Error and Beyond
231. NeurIPS 2024Order-Independence Without Fine Tuning
232. NeurIPS 2024PaCE: Parsimonious Concept Engineering for Large Language Models
233. NeurIPS 2024PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher
234. NeurIPS 2024Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent
235. NeurIPS 2024Parametric model reduction of mean-field and stochastic systems via higher-order action matching
236. NeurIPS 2024Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation
237. NeurIPS 2024PEACE: A Dataset of Pharmaceutical Care for Cancer Pain Analgesia Evaluation and Medication Decision
238. NeurIPS 2024PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator
239. NeurIPS 2024PERIA: Perceive, Reason, Imagine, Act via Holistic Language and Vision Planning for Manipulation
240. NeurIPS 2024Pessimistic Backward Policy for GFlowNets
241. NeurIPS 2024Phased Consistency Models
242. NeurIPS 2024PhoCoLens: Photorealistic and Consistent Reconstruction in Lensless Imaging
243. NeurIPS 2024Piecewise deterministic generative models
244. NeurIPS 2024Poisson Variational Autoencoder
245. NeurIPS 2024Polyhedral Complex Derivation from Piecewise Trilinear Networks
246. NeurIPS 2024Practical Shuffle Coding
247. NeurIPS 2024Pricing and Competition for Generative AI
248. NeurIPS 2024ProEdit: Simple Progression is All You Need for High-Quality 3D Scene Editing
249. NeurIPS 2024Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation
250. NeurIPS 2024Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer

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.