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

900 papers, page 9 of 18

401. ICML 2025Angle Domain Guidance: Latent Diffusion Requires Rotation Rather Than Extrapolation
402. ICML 2025Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions
403. ICML 2025Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
404. ICML 2025AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration
405. ICML 2025Autoencoder-Based Hybrid Replay for Class-Incremental Learning
406. ICML 2025AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders
407. ICML 2025Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
408. ICML 2025Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders
409. ICML 2025Benign Overfitting in Token Selection of Attention Mechanism
410. ICML 2025Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance
411. ICML 2025Beyond Task-Specific Reasoning: A Unified Conditional Generative Framework for Abstract Visual Reasoning
412. ICML 2025BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models
413. ICML 2025Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
414. ICML 2025Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images?
415. ICML 2025CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual Learning
416. ICML 2025Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics
417. ICML 2025Categorical Schrödinger Bridge Matching
418. ICML 2025Censor Dependent Variational Inference
419. ICML 2025CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation
420. ICML 2025COExpander: Adaptive Solution Expansion for Combinatorial Optimization
421. ICML 2025Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
422. ICML 2025Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training
423. ICML 2025Compositional Condition Question Answering in Tabular Understanding
424. ICML 2025Compositional Scene Understanding through Inverse Generative Modeling
425. ICML 2025Compressed Image Generation with Denoising Diffusion Codebook Models
426. ICML 2025Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders
427. ICML 2025Concept Reachability in Diffusion Models: Beyond Dataset Constraints
428. ICML 2025Concept-Centric Token Interpretation for Vector-Quantized Generative Models
429. ICML 2025ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
430. ICML 2025Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
431. ICML 2025Continuous Semi-Implicit Models
432. ICML 2025Continuous Visual Autoregressive Generation via Score Maximization
433. ICML 2025Controlled Generation with Equivariant Variational Flow Matching
434. ICML 2025D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
435. ICML 2025DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space
436. ICML 2025DeFoG: Discrete Flow Matching for Graph Generation
437. ICML 2025Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
438. ICML 2025Density Ratio Estimation with Conditional Probability Paths
439. ICML 2025Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
440. ICML 2025Differentiable Solver Search for Fast Diffusion Sampling
441. ICML 2025Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces
442. ICML 2025Diffusion Adversarial Post-Training for One-Step Video Generation
443. ICML 2025Diffusion Counterfactual Generation with Semantic Abduction
444. ICML 2025Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation
445. ICML 2025Diffusion Sampling Correction via Approximately 10 Parameters
446. ICML 2025Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator
447. ICML 2025Direct Motion Models for Assessing Generated Videos
448. ICML 2025Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions
449. ICML 2025Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data
450. ICML 2025Distillation of Discrete Diffusion through Dimensional Correlations

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.