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 3 of 7

101. NeurIPS 2024Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
102. NeurIPS 2024Exploring DCN-like architecture for fast image generation with arbitrary resolution
103. NeurIPS 2024Extending Video Masked Autoencoders to 128 frames
104. NeurIPS 2024FactorSim: Generative Simulation via Factorized Representation
105. NeurIPS 2024Fast Best-of-N Decoding via Speculative Rejection
106. NeurIPS 2024Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization
107. NeurIPS 2024Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference
108. NeurIPS 2024FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification
109. NeurIPS 2024Few-Shot Diffusion Models Escape the Curse of Dimensionality
110. NeurIPS 2024Few-Shot Task Learning through Inverse Generative Modeling
111. NeurIPS 2024FINALLY: fast and universal speech enhancement with studio-like quality
112. NeurIPS 2024Fine-grained Control of Generative Data Augmentation in IoT Sensing
113. NeurIPS 2024FineStyle: Fine-grained Controllable Style Personalization for Text-to-image Models
114. NeurIPS 2024Fisher Flow Matching for Generative Modeling over Discrete Data
115. NeurIPS 2024Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching
116. NeurIPS 2024FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
117. NeurIPS 2024FouRA: Fourier Low-Rank Adaptation
118. NeurIPS 2024FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention
119. NeurIPS 2024Frequency-aware Generative Models for Multivariate Time Series Imputation
120. NeurIPS 2024GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling
121. NeurIPS 2024GAVEL: Generating Games via Evolution and Language Models
122. NeurIPS 2024GenAI Arena: An Open Evaluation Platform for Generative Models
123. NeurIPS 2024GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing
124. NeurIPS 2024Generalized Eigenvalue Problems with Generative Priors
125. NeurIPS 2024Generating Highly Designable Proteins with Geometric Algebra Flow Matching
126. NeurIPS 2024Generative Adversarial Model-Based Optimization via Source Critic Regularization
127. NeurIPS 2024Generative Forests
128. NeurIPS 2024Generative Fractional Diffusion Models
129. NeurIPS 2024Generative Modelling of Structurally Constrained Graphs
130. NeurIPS 2024Generative Retrieval Meets Multi-Graded Relevance
131. NeurIPS 2024Generative Semi-supervised Graph Anomaly Detection
132. NeurIPS 2024Genetic-guided GFlowNets for Sample Efficient Molecular Optimization
133. NeurIPS 2024GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping
134. NeurIPS 2024GeoLRM: Geometry-Aware Large Reconstruction Model for High-Quality 3D Gaussian Generation
135. NeurIPS 2024Gorilla: Large Language Model Connected with Massive APIs
136. NeurIPS 2024Gradient-free Decoder Inversion in Latent Diffusion Models
137. NeurIPS 2024Graph Diffusion Policy Optimization
138. NeurIPS 2024Grounded Answers for Multi-agent Decision-making Problem through Generative World Model
139. NeurIPS 2024Grounding Multimodal Large Language Models in Actions
140. NeurIPS 2024Group Robust Preference Optimization in Reward-free RLHF
141. NeurIPS 2024GSGAN: Adversarial Learning for Hierarchical Generation of 3D Gaussian Splats
142. NeurIPS 2024GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning
143. NeurIPS 2024GuardT2I: Defending Text-to-Image Models from Adversarial Prompts
144. NeurIPS 2024Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization
145. NeurIPS 2024HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach
146. NeurIPS 2024Hallo3D: Multi-Modal Hallucination Detection and Mitigation for Consistent 3D Content Generation
147. NeurIPS 2024Hamiltonian Score Matching and Generative Flows
148. NeurIPS 2024Harmonizing Visual Text Comprehension and Generation
149. NeurIPS 2024HiCo: Hierarchical Controllable Diffusion Model for Layout-to-image Generation
150. NeurIPS 2024HonestLLM: Toward an Honest and Helpful Large Language Model

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.