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

4,314 papers, page 3 of 87

101. CVPR 2026LuxRemix Lighting Decomposition and Remixing for Indoor Scenes
102. CVPR 2026Making Training-Free Diffusion Segmentors Scale with the Generative Power
103. CVPR 2026MaskDexGrasp Generative Masked Modeling for Part-Aware Dexterous Grasp Synthesis
104. CVPR 2026Masked-Diffusion Autoencoders for 3D Medical Vision Representation Learning
105. CVPR 2026MatchMask Mask-Centric Generative Data Augmentation for Label-Scarce Semantic Segmentation
106. CVPR 2026MatPedia A Universal Generative Foundation for High-Fidelity Material Synthesis
107. CVPR 2026MaxMark High-Capacity Diffusion-Native Watermarking via Robust and Invertible Latent Embedding
108. CVPR 2026MeanFlow Transformers with Representation Autoencoders
109. CVPR 2026MedLIME A Distribution-Aligned and Evidence-Supported Framework for Medical Saliency Explanations
110. CVPR 2026Mind the Generative Details Direct Localized Detail Preference Optimization for
111. CVPR 2026MorphAny3D Unleashing the Power of Structured Latent in 3D Morphing
112. CVPR 2026MSRL Scaling Generative Multimodal Reward Modeling via Multi-Stage Reinforcement Learning
113. CVPR 2026Multi-Patch Global-to-Local Transformer Architecture For Efficient Flow Matching and Diffusion
114. CVPR 2026MV2UV Generating High-quality UV Texture Maps with Multiview Prompts
115. CVPR 2026Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling
116. CVPR 2026NeuROK Generative 4D Neural Object Kinematics
117. CVPR 2026Omni-3DEdit Generalized Versatile 3D Editing in One-Pass
118. CVPR 2026OntoAug Rethinking Generative Data Augmentation via Ontology Guidance
119. CVPR 2026OpenVision 2 A Family of Generative Pretrained Visual Encoders for
120. CVPR 2026Opti-NeuS Neural Reconstruction for Dual-Layered Transparent and Opaque Objects
121. CVPR 2026PGA Prior-free Generative Attack for Practical No-box Scenario
122. CVPR 2026PhyCo Learning Controllable Physical Priors for Generative Motion
123. CVPR 2026PhysVid Physics Aware Local Conditioning for Generative Video Models
124. CVPR 2026PixARMesh Autoregressive Mesh-Native Single-View Scene Reconstruction
125. CVPR 2026PnP-CM Consistency Models as Plug-and-Play Priors for Inverse Problems
126. CVPR 2026POLAR A Portrait OLAT Dataset and Generative Framework for Illumination-Aware
127. CVPR 2026PoseD-Flow Versatile and Guided Flow Matching Model of Human Pose
128. CVPR 2026Rectifying Latent Space for Generative Single-Image Reflection Removal
129. CVPR 2026Recurrent Video Masked Autoencoders
130. CVPR 2026Ref4D-VideoBench Four-Dimensional Reference-Based Evaluation of Text-to-Video Generative Models
131. CVPR 2026Refracting Reality Generating Images with Realistic Transparent Objects
132. CVPR 2026RenderFlow Single-Step Neural Rendering via Flow Matching
133. CVPR 2026Repurposing 3D Generative Model for Autoregressive Layout Generation
134. CVPR 2026Residual Connections Harm Generative Representation Learning
135. CVPR 2026RigMo Unifying Rig and Motion Learning for Generative Animation
136. CVPR 2026RoMo A Large-Scale Richly Organized Dataset and Semantic Taxonomy for
137. CVPR 2026SAGA Source Attribution of Generative AI Videos
138. CVPR 2026SAM 3D 3Dfy Anything in Images
139. CVPR 2026Sculpt4D Generating 4D Shapes via Sparse-Attention Diffusion Transformers
140. CVPR 2026SegCompass Exploring Interpretable Alignment with Sparse Autoencoders for Enhanced Reasoning
141. CVPR 2026SegQuant A Semantics-Aware and Generalizable Quantization Framework for Diffusion Models
142. CVPR 2026SemiGDA Generative Dual-distribution Alignment for Semi-Supervised Medical Image Segmentation
143. CVPR 2026SemLayer Semantic-aware Generative Segmentation and Layer Construction for Abstract Icons
144. CVPR 2026ShowUI-p Flow-based Generative Models as GUI Dexterous Hands
145. CVPR 2026SimLBR Learning to Detect Fake Images by Learning to Detect
146. CVPR 2026SmokeSVD Smoke Reconstruction from A Single View via Progressive Novel
147. CVPR 2026SpaceTimePilot Generative Rendering of Dynamic Scenes Across Space and Time
148. CVPR 2026SparseWorld-TC Trajectory-Conditioned Sparse Occupancy World Model
149. CVPR 2026Stable Mean Flow Lyapunov-Inspired One-Step Flow Matching
150. CVPR 2026Steering Where to Diffuse Generative Modeling of Phenotypic Response Simulation

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.