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 17 of 87

801. ICML 2026Mixtures Closest To A Given Measure: A Semidefinite Programming Approach
802. ICML 2026MMD Guidance: Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance
803. ICML 2026Mode Seeking meets Mean Seeking for Fast Long Video Generation
804. ICML 2026Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport
805. ICML 2026Modelling Attention with Aitchison Geometry: Token Distinguishability and Temperature Scaling
806. ICML 2026MolAlign3D: Enhancing Fixed-Dimensional E(3)-Equivariant Latent Space for High-Fidelity 3D Molecular Reconstruction and Editing
807. ICML 2026MoLoRA: Composable Specialization via Per-Token Adapter Routing
808. ICML 2026Moment Matching Q-Learning
809. ICML 2026MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language Models
810. ICML 2026MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts
811. ICML 2026Motion Attribution for Video Generation
812. ICML 2026Motion-Aware Caching for Efficient Autoregressive Video Generation
813. ICML 2026Motion-Residual Conflict-Aware Time Reversal for Generative Inbetweening
814. ICML 2026MPFM: Cross Multi-Domain Prototype Flow Matching for Log Anomaly Detection
815. ICML 2026MuCO: Generative Peptide Cyclization Empowered by Multi-stage Conformation Optimization
816. ICML 2026Multi-marginal temporal Schrödinger Bridge Matching from unpaired data
817. ICML 2026Multi-Objective Preference Optimization: Improving Human Alignment of Generative Models
818. ICML 2026Multi-Objective Protein Design via Memory-Aware Test-Time Scaling in Diffusion Models
819. ICML 2026Multimarginal flow matching with optimal transport potentials
820. ICML 2026Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
821. ICML 2026MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality
822. ICML 2026NaviCache: Test-Time Self-Calibration Caching for Video Generation
823. ICML 2026Navigating the Energy Landscape of Collaboration: Multi-Agent Communication Graph Generation via Score-Based Diffusion
824. ICML 2026Neural Dispersion on Graphs
825. ICML 2026Nonparametric Data Attribution for Diffusion Models
826. ICML 2026Normalizing Flows with Iterative Denoising
827. ICML 2026Offline Reinforcement Learning with Generative Trajectory Policies
828. ICML 2026OGPO: Sample Efficient Full-Finetuning of Generative Control Policies
829. ICML 2026OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation
830. ICML 2026OMP: One-step Meanflow Policy with Directional Alignment
831. ICML 2026On the Anisotropy of Score-Based Generative Models
832. ICML 2026On the Collapse of Generative Paths: A Criterion and Correction for Diffusion Steering
833. ICML 2026On the Fragility of Data Attribution When Learning Is Distributed
834. ICML 2026On the Generalization in Topology Optimization via Sensitivity-Conditioned Bernoulli Flow Matching
835. ICML 2026On the Relationship Between Activation Outliers and Feature Death in Sparse Autoencoders
836. ICML 2026On the Separability of Information in Diffusion Models
837. ICML 2026One-step Latent-free Image Generation with Pixel Mean Flows
838. ICML 2026One-step Optimal Transport via Regularized Distribution Matching Distillation
839. ICML 2026One-Step Residual Shifting Diffusion for Image Super-Resolution via Distillation
840. ICML 2026OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
841. ICML 2026Opportunistic Expert Activation: Batch-Aware Expert Routing for Faster Decode Without Retraining
842. ICML 2026Optimal Stopping in Latent Diffusion Models
843. ICML 2026Optimality of FSQ Tokens for Continuous Diffusion for Categorical Data with Application to Text-to-Speech
844. ICML 2026Optimizing Few-Step Generation with Adaptive Matching Distillation
845. ICML 2026Optimizing Visual Generative Models via Distribution-wise Rewards
846. ICML 2026Order Matters in Retrosynthesis: Structure-aware Generation via Reaction-Center-Guided Discrete Flow Matching
847. ICML 2026Overclocking Electrostatic Generative Models
848. ICML 2026OVLR: Efficient, Scalable, and Robust Training via Output-Level Variance-Reduced Likelihood Ratio
849. ICML 2026PADS-TAL: Padding-Annealed Diffusion Sampling in Text-Aware Latent Space for Robust and Diverse Text-to-Music Generation
850. ICML 2026Parameter Manifold Purification

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.