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 39 of 87

1901. ICML 2025Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity
1902. ICML 2025Fast Video Generation with Sliding Tile Attention
1903. ICML 2025Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
1904. ICML 2025Field Matching: an Electrostatic Paradigm to Generate and Transfer Data
1905. ICML 2025FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
1906. ICML 2025FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation
1907. ICML 2025FlexiClip: Locality-Preserving Free-Form Character Animation
1908. ICML 2025FlexTok: Resampling Images into 1D Token Sequences of Flexible Length
1909. ICML 2025FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching
1910. ICML 2025FrameBridge: Improving Image-to-Video Generation with Bridge Models
1911. ICML 2025From Mechanistic Interpretability to Mechanistic Biology: Training, Evaluating, and Interpreting Sparse Autoencoders on Protein Language Models
1912. ICML 2025G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibration
1913. ICML 2025Gaussian Mixture Flow Matching Models
1914. ICML 2025Generalized Interpolating Discrete Diffusion
1915. ICML 2025Generative Audio Language Modeling with Continuous-valued Tokens and Masked Next-Token Prediction
1916. ICML 2025Generative Data Mining with Longtail-Guided Diffusion
1917. ICML 2025Generative Human Trajectory Recovery via Embedding-Space Conditional Diffusion
1918. ICML 2025Generative Intervention Models for Causal Perturbation Modeling
1919. ICML 2025Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning
1920. ICML 2025Generative Point Cloud Registration
1921. ICML 2025GenZSL: Generative Zero-Shot Learning Via Inductive Variational Autoencoder
1922. ICML 2025Geometric Generative Modeling with Noise-Conditioned Graph Networks
1923. ICML 2025Geometric Representation Condition Improves Equivariant Molecule Generation
1924. ICML 2025Geometry Informed Tokenization of Molecules for Language Model Generation
1925. ICML 2025Geometry-Informed Neural Networks
1926. ICML 2025GMAIL: Generative Modality Alignment for generated Image Learning
1927. ICML 2025Graph Generative Pre-trained Transformer
1928. ICML 2025GraphGPT: Generative Pre-trained Graph Eulerian Transformer
1929. ICML 2025Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres
1930. ICML 2025HashAttention: Semantic Sparsity for Faster Inference
1931. ICML 2025Hessian Geometry of Latent Space in Generative Models
1932. ICML 2025Highly Compressed Tokenizer Can Generate Without Training
1933. ICML 2025How Compositional Generalization and Creativity Improve as Diffusion Models are Trained
1934. ICML 2025How to Evaluate and Mitigate IP Infringement in Visual Generative AI?
1935. ICML 2025How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects
1936. ICML 2025Hyper-Transforming Latent Diffusion Models
1937. ICML 2025I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models
1938. ICML 2025Identifiable Object Representations under Spatial Ambiguities
1939. ICML 2025IMPACT: Iterative Mask-based Parallel Decoding for Text-to-Audio Generation with Diffusion Modeling
1940. ICML 2025Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization Scheme
1941. ICML 2025Improving Consistency Models with Generator-Augmented Flows
1942. ICML 2025Improving Flow Matching by Aligning Flow Divergence
1943. ICML 2025Improving the Diffusability of Autoencoders
1944. ICML 2025Improving the Scaling Laws of Synthetic Data with Deliberate Practice
1945. ICML 2025IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction
1946. ICML 2025Inductive Moment Matching
1947. ICML 2025Inference-Time Alignment of Diffusion Models with Direct Noise Optimization
1948. ICML 2025InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network Inference
1949. ICML 2025INRFlow: Flow Matching for INRs in Ambient Space
1950. ICML 2025Interpreting CLIP with Hierarchical Sparse Autoencoders

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.