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 47 of 87

2301. NeurIPS 2025The ML.ENERGY Benchmark: Toward Automated Inference Energy Measurement and Optimization
2302. NeurIPS 2025ThermalGen: Style-Disentangled Flow-Based Generative Models for RGB-to-Thermal Image Translation
2303. NeurIPS 2025Towards a Pairwise Ranking Model with Orderliness and Monotonicity for Label Enhancement
2304. NeurIPS 2025Towards A Translative Model of Sperm Whale Vocalization
2305. NeurIPS 2025Tracing the Roots: Leveraging Temporal Dynamics in Diffusion Trajectories for Origin Attribution
2306. NeurIPS 2025Training-Free Safe Denoisers for Safe Use of Diffusion Models
2307. NeurIPS 2025Transferring Linear Features Across Language Models With Model Stitching
2308. NeurIPS 2025Transformer Key-Value Memories Are Nearly as Interpretable as Sparse Autoencoders
2309. NeurIPS 2025Transformers for Mixed-type Event Sequences
2310. NeurIPS 2025Transition Matching: Scalable and Flexible Generative Modeling
2311. NeurIPS 2025TreeGen: A Bayesian Generative Model for Hierarchies
2312. NeurIPS 2025UMAMI: Unifying Masked Autoregressive Models and Deterministic Rendering for View Synthesis
2313. NeurIPS 2025un$^2$CLIP: Improving CLIP's Visual Detail Capturing Ability via Inverting unCLIP
2314. NeurIPS 2025Unextractable Protocol Models: Collaborative Training and Inference without Weight Materialization
2315. NeurIPS 2025Universal Video Temporal Grounding with Generative Multi-modal Large Language Models
2316. NeurIPS 2025Unveiling Concept Attribution in Diffusion Models
2317. NeurIPS 2025UtilGen: Utility-Centric Generative Data Augmentation with Dual-Level Task Adaptation
2318. NeurIPS 2025Video Diffusion Models Excel at Tracking Similar-Looking Objects Without Supervision
2319. NeurIPS 2025Virtual Fitting Room: Generating Arbitrarily Long Videos of Virtual Try-On from a Single Image
2320. NeurIPS 2025VisDiff: SDF-Guided Polygon Generation for Visibility Reconstruction, Characterization and Recognition
2321. NeurIPS 2025Visual Jenga: Discovering Object Dependencies via Counterfactual Inpainting
2322. NeurIPS 2025Wasserstein Convergence of Critically Damped Langevin Diffusions
2323. NeurIPS 2025What's Producible May Not Be Reachable: Measuring the Steerability of Generative Models
2324. NeurIPS 2025When and how can inexact generative models still sample from the data manifold?
2325. NeurIPS 2025When Do Transformers Outperform Feedforward and Recurrent Networks? A Statistical Perspective
2326. NeurIPS 2025When Models Don’t Collapse: On the Consistency of Iterative MLE
2327. NeurIPS 2025Where and How to Perturb: On the Design of Perturbation Guidance in Diffusion and Flow Models
2328. NeurIPS 2025Why Diffusion Models Don’t Memorize: The Role of Implicit Dynamical Regularization in Training
2329. NeurIPS 2025Why Knowledge Distillation Works in Generative Models: A Minimal Working Explanation
2330. NeurIPS 2025WritingBench: A Comprehensive Benchmark for Generative Writing
2331. CVPR 20243D Paintbrush: Local Stylization of 3D Shapes with Cascaded Score Distillation
2332. CVPR 2024A Generative Approach for Wikipedia-Scale Visual Entity Recognition
2333. CVPR 2024AiOS: All-in-One-Stage Expressive Human Pose and Shape Estimation
2334. CVPR 2024An Edit Friendly DDPM Noise Space: Inversion and Manipulations
2335. CVPR 2024Anomaly Score: Evaluating Generative Models and Individual Generated Images based on Complexity and Vulnerability
2336. CVPR 2024ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe
2337. CVPR 2024Boosting Flow-based Generative Super-Resolution Models via Learned Prior
2338. CVPR 2024Building Bridges across Spatial and Temporal Resolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion Model
2339. CVPR 2024CAT-DM: Controllable Accelerated Virtual Try-on with Diffusion Model
2340. CVPR 2024CityDreamer: Compositional Generative Model of Unbounded 3D Cities
2341. CVPR 2024Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation
2342. CVPR 2024CrossMAE: Cross-Modality Masked Autoencoders for Region-Aware Audio-Visual Pre-Training
2343. CVPR 2024Deciphering 'What' and 'Where' Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations
2344. CVPR 2024Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation
2345. CVPR 2024Deep Generative Model based Rate-Distortion for Image Downscaling Assessment
2346. CVPR 2024DeepCache: Accelerating Diffusion Models for Free
2347. CVPR 2024DetCLIPv3: Towards Versatile Generative Open-vocabulary Object Detection
2348. CVPR 2024DetDiffusion: Synergizing Generative and Perceptive Models for Enhanced Data Generation and Perception
2349. CVPR 2024DiffuScene: Denoising Diffusion Models for Generative Indoor Scene Synthesis
2350. CVPR 2024Diffusion Handles Enabling 3D Edits for Diffusion Models by Lifting Activations to 3D

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.