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 7 of 87

301. ICLR 2026Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later
302. ICLR 2026GeomMotif: A Benchmark for Arbitrary Geometric Preservation in Protein Generation
303. ICLR 2026GGBall: Graph Generative Model on Poincaré Ball
304. ICLR 2026GoR: A Unified and Extensible Generative Framework for Ordinal Regression
305. ICLR 2026GRACE: Generative Representation Learning via Contrastive Policy Optimization
306. ICLR 2026Gradient-Aligned Calibration for Post-Training Quantization of Diffusion Models
307. ICLR 2026Grounding and Enhancing Informativeness and Utility in Dataset Distillation
308. ICLR 2026Guidance Watermarking for Diffusion Models
309. ICLR 2026H2OFlow: Grounding Human-Object Affordances with 3D Generative Models and Dense Diffused Flows
310. ICLR 2026Hierarchical Concept-based Interpretable Models
311. ICLR 2026High-dimensional Analysis of Synthetic Data Selection
312. ICLR 2026HiGS: History-Guided Sampling for Plug-and-Play Enhancement of Diffusion Models
313. ICLR 2026HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Series
314. ICLR 2026HoloPart: Generative 3D Part Amodal Segmentation
315. ICLR 2026How to Square Tensor Networks and Circuits Without Squaring Them
316. ICLR 2026Human Uncertainty-Aware Data Selection and Automatic Labeling in Visual Question Answering
317. ICLR 2026Identifiability and recoverability in self-supervised models
318. ICLR 2026Implicit Regularisation in Diffusion Models: An Algorithm-Dependent Generalisation Analysis
319. ICLR 2026Improving Black-Box Generative Attacks via Generator Semantic Consistency
320. ICLR 2026Improving Discrete Diffusion Unmasking Policies Beyond Explicit Reference Policies
321. ICLR 2026InfBaGel: Human-Object-Scene Interaction Generation with Dynamic Perception and Iterative Refinement
322. ICLR 2026Inference-Time Scaling of Discrete Diffusion Models via Importance Weighting and Optimal Proposal Design
323. ICLR 2026InfoBridge: Mutual Information estimation via Bridge Matching
324. ICLR 2026Interaction Field Matching: Overcoming Limitations of Electrostatic Models
325. ICLR 2026Interp3D: Correspondence-aware Interpolation for Generative Textured 3D Morphing
326. ICLR 2026Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models
327. ICLR 2026LABEL-FREE MITIGATION OF SPURIOUS CORRELATIONS IN VLMS USING SPARSE AUTOENCODERS
328. ICLR 2026Latent Denoising Makes Good Tokenizers
329. ICLR 2026Latent Diffusion Model without Variational Autoencoder
330. ICLR 2026Latent Stochastic Interpolants
331. ICLR 2026Latent Wavelet Diffusion For Ultra High-Resolution Image Synthesis
332. ICLR 2026LayerSync: Self-aligning Intermediate Layers
333. ICLR 2026Learn to Guide Your Diffusion Model
334. ICLR 2026Learnable Sparsity for Vision Generative Models
335. ICLR 2026Learning a distance measure from the information-estimation geometry of data
336. ICLR 2026Learning Correlated Reward Models: Statistical Barriers and Opportunities
337. ICLR 2026Learning multimodal dictionary decompositions with group-sparse autoencoders
338. ICLR 2026Learning on a Razor’s Edge: Identifiability and Singularity of Polynomial Neural Networks
339. ICLR 2026Learning Retrieval Models with Sparse Autoencoders
340. ICLR 2026Let LLMs Speak Embedding Languages: Generative Text Embeddings via Iterative Contrastive Refinement
341. ICLR 2026Light-X: Generative 4D Video Rendering with Camera and Illumination Control
342. ICLR 2026LingoLoop Attack: Trapping MLLMs via Linguistic Context and State Entrapment into Endless Loops
343. ICLR 2026LLM Pretraining with Continuous Concepts
344. ICLR 2026LLMs Can Hide Text in Other Text of the Same Length
345. ICLR 2026Loopholing Discrete Diffusion: Deterministic Bypass of the Sampling Wall
346. ICLR 2026LS-Merge: Merging Language Models in Latent Space
347. ICLR 2026Market Games for Generative Models: Equilibria, Welfare, and Strategic Entry
348. ICLR 2026MAS$^2$: Self-Generative, Self-Configuring, Self-Rectifying Multi-Agent Systems
349. ICLR 2026Masked Generative Policy for Robotic Control
350. ICLR 2026Massive Memorization with Hundreds of Trillions of Parameters for Sequential Transducer Generative Recommenders

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.