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 2 of 6

51. ICML 2025DeFoG: Discrete Flow Matching for Graph Generation
52. ICML 2025Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
53. ICML 2025Density Ratio Estimation with Conditional Probability Paths
54. ICML 2025Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
55. ICML 2025Differentiable Solver Search for Fast Diffusion Sampling
56. ICML 2025Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces
57. ICML 2025Diffusion Adversarial Post-Training for One-Step Video Generation
58. ICML 2025Diffusion Counterfactual Generation with Semantic Abduction
59. ICML 2025Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation
60. ICML 2025Diffusion Sampling Correction via Approximately 10 Parameters
61. ICML 2025Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator
62. ICML 2025Direct Motion Models for Assessing Generated Videos
63. ICML 2025Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions
64. ICML 2025Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data
65. ICML 2025Distillation of Discrete Diffusion through Dimensional Correlations
66. ICML 2025DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
67. ICML 2025Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
68. ICML 2025Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion
69. ICML 2025EasyInv: Toward Fast and Better DDIM Inversion
70. ICML 2025EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM
71. ICML 2025Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image Manipulation
72. ICML 2025Effective and Efficient Masked Image Generation Models
73. ICML 2025Efficient Diffusion Models for Symmetric Manifolds
74. ICML 2025Efficient Fine-Grained Guidance for Diffusion Model Based Symbolic Music Generation
75. ICML 2025Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
76. ICML 2025Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow
77. ICML 2025Efficiently Access Diffusion Fisher: Within the Outer Product Span Space
78. ICML 2025Elucidating Flow Matching ODE Dynamics via Data Geometry and Denoisers
79. ICML 2025Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation
80. ICML 2025Ensemble Distribution Distillation via Flow Matching
81. ICML 2025Epsilon-VAE: Denoising as Visual Decoding
82. ICML 2025EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
83. ICML 2025Ergodic Generative Flows
84. ICML 2025Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representations
85. ICML 2025Exponential Family Variational Flow Matching for Tabular Data Generation
86. ICML 2025Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity
87. ICML 2025Fast Video Generation with Sliding Tile Attention
88. ICML 2025Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
89. ICML 2025Field Matching: an Electrostatic Paradigm to Generate and Transfer Data
90. ICML 2025FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
91. ICML 2025FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation
92. ICML 2025FlexiClip: Locality-Preserving Free-Form Character Animation
93. ICML 2025FlexTok: Resampling Images into 1D Token Sequences of Flexible Length
94. ICML 2025FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching
95. ICML 2025FrameBridge: Improving Image-to-Video Generation with Bridge Models
96. ICML 2025From Mechanistic Interpretability to Mechanistic Biology: Training, Evaluating, and Interpreting Sparse Autoencoders on Protein Language Models
97. ICML 2025G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibration
98. ICML 2025Gaussian Mixture Flow Matching Models
99. ICML 2025Generalized Interpolating Discrete Diffusion
100. ICML 2025Generative Audio Language Modeling with Continuous-valued Tokens and Masked Next-Token Prediction

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.