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 11 of 18

501. ICML 2025Hessian Geometry of Latent Space in Generative Models
502. ICML 2025Highly Compressed Tokenizer Can Generate Without Training
503. ICML 2025How Compositional Generalization and Creativity Improve as Diffusion Models are Trained
504. ICML 2025How to Evaluate and Mitigate IP Infringement in Visual Generative AI?
505. ICML 2025How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects
506. ICML 2025Hyper-Transforming Latent Diffusion Models
507. ICML 2025I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models
508. ICML 2025Identifiable Object Representations under Spatial Ambiguities
509. ICML 2025IMPACT: Iterative Mask-based Parallel Decoding for Text-to-Audio Generation with Diffusion Modeling
510. ICML 2025Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization Scheme
511. ICML 2025Improving Consistency Models with Generator-Augmented Flows
512. ICML 2025Improving Flow Matching by Aligning Flow Divergence
513. ICML 2025Improving the Diffusability of Autoencoders
514. ICML 2025Improving the Scaling Laws of Synthetic Data with Deliberate Practice
515. ICML 2025IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction
516. ICML 2025Inductive Moment Matching
517. ICML 2025Inference-Time Alignment of Diffusion Models with Direct Noise Optimization
518. ICML 2025InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network Inference
519. ICML 2025INRFlow: Flow Matching for INRs in Ambient Space
520. ICML 2025Interpreting CLIP with Hierarchical Sparse Autoencoders
521. ICML 2025Introducing 3D Representation for Dense Volume-to-Volume Translation via Score Fusion
522. ICML 2025Inverse Bridge Matching Distillation
523. ICML 2025Inverse Flow and Consistency Models
524. ICML 2025Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo
525. ICML 2025Inverse problems with experiment-guided AlphaFold
526. ICML 2025IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models
527. ICML 2025Is Noise Conditioning Necessary for Denoising Generative Models?
528. ICML 2025Kinetic Langevin Diffusion for Crystalline Materials Generation
529. ICML 2025LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection
530. ICML 2025Latent Thought Models with Variational Bayes Inference-Time Computation
531. ICML 2025Learning Extrapolative Sequence Transformations from Markov Chains
532. ICML 2025Learning Latent Graph Structures and their Uncertainty
533. ICML 2025Learning Monotonic Probabilities with a Generative Cost Model
534. ICML 2025Learning Multi-Level Features with Matryoshka Sparse Autoencoders
535. ICML 2025Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
536. ICML 2025Learning to Match Unpaired Data with Minimum Entropy Coupling
537. ICML 2025Learning to Quantize for Training Vector-Quantized Networks
538. ICML 2025Learnings from Scaling Visual Tokenizers for Reconstruction and Generation
539. ICML 2025LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
540. ICML 2025LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data
541. ICML 2025Low-Rank Adapting Models for Sparse Autoencoders
542. ICML 2025Masked Autoencoders Are Effective Tokenizers for Diffusion Models
543. ICML 2025Masked Generative Nested Transformers with Decode Time Scaling
544. ICML 2025MDDM: Practical Message-Driven Generative Image Steganography Based on Diffusion Models
545. ICML 2025Measuring Diversity: Axioms and Challenges
546. ICML 2025Mechanisms of Projective Composition of Diffusion Models
547. ICML 2025MGD$^3$ : Mode-Guided Dataset Distillation using Diffusion Models
548. ICML 2025MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance
549. ICML 2025MissScore: High-Order Score Estimation in the Presence of Missing Data
550. ICML 2025MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES

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.