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

604 papers, page 7 of 13

301. ICML 2026M-Star: Markovian Projection of Star-Shaped Diffusion for Exponential Family Distributions
302. ICML 2026MAD: Manifold Attracted Diffusion
303. ICML 2026Magnitude Distance: A Geometric Measure of Dataset Similarity
304. ICML 2026MAMBO-G: Magnitude-Aware Mitigation for Boosted Guidance
305. ICML 2026Manifold-Aware Perturbations for Constrained Generative Modeling
306. ICML 2026Manifold-Optimal Guidance: A Unified Riemannian Control View of Diffusion Guidance
307. ICML 2026MarketSim: Simulating Stock Markets with Large-Scale Generative Agents
308. ICML 2026MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks
309. ICML 2026Maximum-Likelihood Learning of Latent Dynamics Without Reconstruction
310. ICML 2026Mean Flow Distillation: Robust and Stable Distillation for Flow Matching Models
311. ICML 2026Measurement-Consistent Langevin Corrector for Stabilizing Latent Diffusion Inverse Problem Solvers
312. ICML 2026MEDUSA: Motion Elimination in Diffusion Using Spectral Attack
313. ICML 2026MemoryLLM: Plug-n-Play Interpretable Feed-Forward Memory for Transformers
314. ICML 2026Meta Flow Maps enable scalable reward alignment
315. ICML 2026Meta-iLaD: Identifiable Latent Dynamics via Meta-Learning of Dynamics Environments
316. ICML 2026MetaOthello: A Controlled Study of Multiple World Models in Transformers
317. ICML 2026MidSteer: Optimal Affine Framework for Steering Generative Models
318. ICML 2026Mind Your Entropy: From Maximum Entropy to Trajectory Entropy-Constrained RL
319. ICML 2026Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching
320. ICML 2026MIRO: MultI-Reward cOnditioned pretraining improves T2I quality and efficiency
321. ICML 2026MIST: Moment-Aligned Invariant Stability Transform for Robust Flow Matching
322. ICML 2026Mitigating Noise-Induced Layout Priors for Object Counting in Diffusion Models
323. ICML 2026Mitigating the Contractivity Trap in Diffusion ODEs via Stein Stabilization
324. ICML 2026Mixtures Closest To A Given Measure: A Semidefinite Programming Approach
325. ICML 2026MMD Guidance: Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance
326. ICML 2026Mode Seeking meets Mean Seeking for Fast Long Video Generation
327. ICML 2026Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport
328. ICML 2026Modelling Attention with Aitchison Geometry: Token Distinguishability and Temperature Scaling
329. ICML 2026MolAlign3D: Enhancing Fixed-Dimensional E(3)-Equivariant Latent Space for High-Fidelity 3D Molecular Reconstruction and Editing
330. ICML 2026MoLoRA: Composable Specialization via Per-Token Adapter Routing
331. ICML 2026Moment Matching Q-Learning
332. ICML 2026MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language Models
333. ICML 2026MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts
334. ICML 2026Motion Attribution for Video Generation
335. ICML 2026Motion-Aware Caching for Efficient Autoregressive Video Generation
336. ICML 2026Motion-Residual Conflict-Aware Time Reversal for Generative Inbetweening
337. ICML 2026MPFM: Cross Multi-Domain Prototype Flow Matching for Log Anomaly Detection
338. ICML 2026MuCO: Generative Peptide Cyclization Empowered by Multi-stage Conformation Optimization
339. ICML 2026Multi-marginal temporal Schrödinger Bridge Matching from unpaired data
340. ICML 2026Multi-Objective Preference Optimization: Improving Human Alignment of Generative Models
341. ICML 2026Multi-Objective Protein Design via Memory-Aware Test-Time Scaling in Diffusion Models
342. ICML 2026Multimarginal flow matching with optimal transport potentials
343. ICML 2026Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
344. ICML 2026MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality
345. ICML 2026NaviCache: Test-Time Self-Calibration Caching for Video Generation
346. ICML 2026Navigating the Energy Landscape of Collaboration: Multi-Agent Communication Graph Generation via Score-Based Diffusion
347. ICML 2026Neural Dispersion on Graphs
348. ICML 2026Nonparametric Data Attribution for Diffusion Models
349. ICML 2026Normalizing Flows with Iterative Denoising
350. ICML 2026Offline Reinforcement Learning with Generative Trajectory Policies

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.