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 21 of 87

1001. ICML 2026Text Generation as Continuous Latent Dynamics via Reinforcement Learning
1002. ICML 2026The Accumulation of Score Estimation Error in Diffusion Models
1003. ICML 2026The Convergent Representation of Contrastive Vision-Language Models: Geometry, Modality Gap and Shared Space Alignment
1004. ICML 2026The Data Manifold under the Microscope
1005. ICML 2026The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms
1006. ICML 2026The Interplay Between Interpolation and Aggregation in Regression: Optimal Sample Complexity
1007. ICML 2026The Latent Color Subspace: Emergent Order in High-Dimensional Chaos
1008. ICML 2026The Velocity Deficit: Initial Energy Injection for Flow Matching
1009. ICML 2026Thinking with Geometry: Active Geometry Integration for Spatial Reasoning
1010. ICML 2026Threshold-Guided Optimization for Visual Generative Models
1011. ICML 2026Tightening the Score Matching Gap for Diffusion Models
1012. ICML 2026Tilt Matching for Scalable Sampling and Fine-Tuning
1013. ICML 2026Time-Conditioned Foreseeing: An EHR-Specific Foundation Model for Irregular Dynamics and Calendrical Time
1014. ICML 2026Timestep Rescheduling in Diffusion Inversion
1015. ICML 2026TMD-Bench: A Multi-Level Evaluation Paradigm for Music–Dance Co-Generation
1016. ICML 2026Toward Identifiable Sparse Autoencoders
1017. ICML 2026Towards A Generative Protein Evolution Machine with DPLM-Evo
1018. ICML 2026Towards Efficient and Expressive Offline RL via Flow-Anchored Noise-conditioned Q-Learning
1019. ICML 2026Towards Generative Graph Matching for Graph Edit Distance Computation
1020. ICML 2026Towards Spectroscopy: Susceptibility Clusters in Language Models
1021. ICML 2026Towards Understanding Continual Factual Knowledge Acquisition of Language Models: From Theory to Algorithm
1022. ICML 2026Training-Free Adaptation of Diffusion Models via Doob's $h$-Transform
1023. ICML 2026Training-Free Bayesian Filtering with Generative Emulators
1024. ICML 2026Training-Free Rate-Distortion-Perception Traversal With Diffusion
1025. ICML 2026Training-Free Vector Quantization via Gaussian VAEs
1026. ICML 2026Trajectory Consistency for One-Step Generation on Euler Mean Flows
1027. ICML 2026Trajectory Stitching for Solving Inverse Problems with Flow-Based Models
1028. ICML 2026Trajectory-Aware Spiking DiTs Conversion via Membrane Potential Error-Feedback
1029. ICML 2026TransLight: Image-Guided Customized Lighting Control with Generative Decoupling
1030. ICML 2026Trees to Flows and Back: Unifying Decision Trees and Diffusion Models
1031. ICML 2026Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules
1032. ICML 2026TRIM: Token-wise Attention-Derived Saliency for Data-Efficient Instruction Tuning
1033. ICML 2026Twins: Learn to Predict Unified Representations with Focal Loss
1034. ICML 2026Two Calm Ends and the Wild Middle: A Geometric Picture of Memorization in Diffusion Models
1035. ICML 2026Two-Parameter Flows for Learning Population Dynamics of Physical Systems
1036. ICML 2026UDM-GRPO: Stable and Efficient Group Relative Policy Optimization for Uniform Discrete Diffusion Models
1037. ICML 2026Uncovering Competency Gaps in Large Language Models and Their Benchmarks
1038. ICML 2026Understanding LoRA as Knowledge Memory: An Empirical Analysis
1039. ICML 2026Understanding Multimodal Learning: A Loss Landscape Smoothness Perspective
1040. ICML 2026Understanding Transfer Learning of RNA Foundation Models on Downstream Tasks
1041. ICML 2026Unfolding Generative Flows with Koopman Operators: Trajectory-Preserving Linearization
1042. ICML 2026UnHype: CLIP-Guided Hypernetworks for Dynamic LoRA Unlearning
1043. ICML 2026UniFLoW: Universal Multi-Modal Federated LoRA Fine-Tuning Framework with Analytical Aggregation
1044. ICML 2026Unifying Masked Diffusion Models with Various Generation Orders and Beyond
1045. ICML 2026Unlearning in Diffusion Models: A Unified Framework with KL Divergence and Likelihood Constraints
1046. ICML 2026Unpaired Visual Editing with Self-Consistent Flow Matching
1047. ICML 2026Unsupervised Disentanglement Without Compromises : How Functional Orthogonality Enforces Identifiability
1048. ICML 2026Unveiling And Addressing Dimensional Collapse In Vector Quantization Models Via Codebook Regularization
1049. ICML 2026Value-as-Return: A Two-Stage Framework to Align on the Optimal Score Function
1050. ICML 2026VAnim: Rendering-Aware Sparse State Modeling for Structure-Preserving Vector Animation

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.