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 7 of 18

301. ICLR 2025PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
302. ICLR 2025PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
303. ICLR 2025Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks
304. ICLR 2025PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
305. ICLR 2025PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
306. ICLR 2025Probing the Latent Hierarchical Structure of Data via Diffusion Models
307. ICLR 2025Progressive Compression with Universally Quantized Diffusion Models
308. ICLR 2025Proteina: Scaling Flow-based Protein Structure Generative Models
309. ICLR 2025ProtoSnap: Prototype Alignment For Cuneiform Signs
310. ICLR 2025QA-Calibration of Language Model Confidence Scores
311. ICLR 2025Quality Measures for Dynamic Graph Generative Models
312. ICLR 2025Rapid Selection and Ordering of In-Context Demonstrations via Prompt Embedding Clustering
313. ICLR 2025RB-Modulation: Training-Free Stylization using Reference-Based Modulation
314. ICLR 2025Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow
315. ICLR 2025ReGen: Generative Robot Simulation via Inverse Design
316. ICLR 2025Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds
317. ICLR 2025RelitLRM: Generative Relightable Radiance for Large Reconstruction Models
318. ICLR 2025Representative Guidance: Diffusion Model Sampling with Coherence
319. ICLR 2025Residual Stream Analysis with Multi-Layer SAEs
320. ICLR 2025Restructuring Vector Quantization with the Rotation Trick
321. ICLR 2025Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
322. ICLR 2025Rethinking Artistic Copyright Infringements In the Era Of Text-to-Image Generative Models
323. ICLR 2025Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
324. ICLR 2025Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words
325. ICLR 2025Rethinking Visual Counterfactual Explanations Through Region Constraint
326. ICLR 2025Risk-Sensitive Diffusion: Robustly Optimizing Diffusion Models with Noisy Samples
327. ICLR 2025Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport
328. ICLR 2025RouteLLM: Learning to Route LLMs from Preference Data
329. ICLR 2025Sample then Identify: A General Framework for Risk Control and Assessment in Multimodal Large Language Models
330. ICLR 2025Scaling and evaluating sparse autoencoders
331. ICLR 2025Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models
332. ICLR 2025Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
333. ICLR 2025Semantic Image Inversion and Editing using Rectified Stochastic Differential Equations
334. ICLR 2025Shallow diffusion networks provably learn hidden low-dimensional structure
335. ICLR 2025Simple ReFlow: Improved Techniques for Fast Flow Models
336. ICLR 2025Simplifying, Stabilizing and Scaling Continuous-time Consistency Models
337. ICLR 2025Sparse Autoencoders Do Not Find Canonical Units of Analysis
338. ICLR 2025Sparse autoencoders reveal selective remapping of visual concepts during adaptation
339. ICLR 2025Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models
340. ICLR 2025Stiefel Flow Matching for Moment-Constrained Structure Elucidation
341. ICLR 2025Streamlining Redundant Layers to Compress Large Language Models
342. ICLR 2025SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency
343. ICLR 2025Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
344. ICLR 2025Sylber: Syllabic Embedding Representation of Speech from Raw Audio
345. ICLR 2025SyllableLM: Learning Coarse Semantic Units for Speech Language Models
346. ICLR 2025SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups
347. ICLR 2025Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
348. ICLR 2025T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching
349. ICLR 2025TabWak: A Watermark for Tabular Diffusion Models
350. ICLR 2025Text-to-Image Rectified Flow as Plug-and-Play Priors

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.