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 10 of 18

451. ICML 2025DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
452. ICML 2025Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
453. ICML 2025Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion
454. ICML 2025EasyInv: Toward Fast and Better DDIM Inversion
455. ICML 2025EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM
456. ICML 2025Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image Manipulation
457. ICML 2025Effective and Efficient Masked Image Generation Models
458. ICML 2025Efficient Diffusion Models for Symmetric Manifolds
459. ICML 2025Efficient Fine-Grained Guidance for Diffusion Model Based Symbolic Music Generation
460. ICML 2025Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
461. ICML 2025Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow
462. ICML 2025Efficiently Access Diffusion Fisher: Within the Outer Product Span Space
463. ICML 2025Elucidating Flow Matching ODE Dynamics via Data Geometry and Denoisers
464. ICML 2025Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation
465. ICML 2025Ensemble Distribution Distillation via Flow Matching
466. ICML 2025Epsilon-VAE: Denoising as Visual Decoding
467. ICML 2025EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
468. ICML 2025Ergodic Generative Flows
469. ICML 2025Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representations
470. ICML 2025Exponential Family Variational Flow Matching for Tabular Data Generation
471. ICML 2025Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity
472. ICML 2025Fast Video Generation with Sliding Tile Attention
473. ICML 2025Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
474. ICML 2025Field Matching: an Electrostatic Paradigm to Generate and Transfer Data
475. ICML 2025FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
476. ICML 2025FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation
477. ICML 2025FlexiClip: Locality-Preserving Free-Form Character Animation
478. ICML 2025FlexTok: Resampling Images into 1D Token Sequences of Flexible Length
479. ICML 2025FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching
480. ICML 2025FrameBridge: Improving Image-to-Video Generation with Bridge Models
481. ICML 2025From Mechanistic Interpretability to Mechanistic Biology: Training, Evaluating, and Interpreting Sparse Autoencoders on Protein Language Models
482. ICML 2025G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibration
483. ICML 2025Gaussian Mixture Flow Matching Models
484. ICML 2025Generalized Interpolating Discrete Diffusion
485. ICML 2025Generative Audio Language Modeling with Continuous-valued Tokens and Masked Next-Token Prediction
486. ICML 2025Generative Data Mining with Longtail-Guided Diffusion
487. ICML 2025Generative Human Trajectory Recovery via Embedding-Space Conditional Diffusion
488. ICML 2025Generative Intervention Models for Causal Perturbation Modeling
489. ICML 2025Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning
490. ICML 2025Generative Point Cloud Registration
491. ICML 2025GenZSL: Generative Zero-Shot Learning Via Inductive Variational Autoencoder
492. ICML 2025Geometric Generative Modeling with Noise-Conditioned Graph Networks
493. ICML 2025Geometric Representation Condition Improves Equivariant Molecule Generation
494. ICML 2025Geometry Informed Tokenization of Molecules for Language Model Generation
495. ICML 2025Geometry-Informed Neural Networks
496. ICML 2025GMAIL: Generative Modality Alignment for generated Image Learning
497. ICML 2025Graph Generative Pre-trained Transformer
498. ICML 2025GraphGPT: Generative Pre-trained Graph Eulerian Transformer
499. ICML 2025Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres
500. ICML 2025HashAttention: Semantic Sparsity for Faster Inference

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.