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

1,304 papers, page 6 of 27

251. ICML 2026Information-Theoretic Generalization Bounds for VAEs: A Role of Encoder and Latent Variable
252. ICML 2026InfVSR: Toward Consistency-Driven Streaming Generative Video Super-Resolution
253. ICML 2026Insertion Based Sequence Generation with Learnable Order Dynamics
254. ICML 2026INT vs. FP: A Comprehensive Study of Fine-Grained Low-bit Quantization Formats
255. ICML 2026Integrated Episodic and Semantic Memory via Modulating Transformer FeedForward Layers
256. ICML 2026Interpretable Embeddings with Sparse Autoencoders: A Data Analysis Toolkit
257. ICML 2026Interpreting Genomic Language Models using Sparse Autoencoders
258. ICML 2026Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization
259. ICML 2026Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning
260. ICML 2026Is Generation Required for Data-Efficient Perception?
261. ICML 2026Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models
262. ICML 2026Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits
263. ICML 2026Just Y-Prediction: Enabling Historical Cumulative Inconsistency in Label Diffusion for Learning with Noisy Label
264. ICML 2026KIStego: Key-Independent Secure Image Distribution via Bipartite Structural Invariants
265. ICML 2026Kuramoto Oscillatory Phase Encoding: Neuro-inspired Synchronization for Improved Learning Efficiency
266. ICML 2026Language Generation in the Limit: Complexity Barriers and Implications for Learning
267. ICML 2026Large-capacity and Receiver Authenticable Generative Image Steganography
268. ICML 2026Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions
269. ICML 2026Latent-Guided Cooperative Energy-Based Models
270. ICML 2026LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer
271. ICML 2026LayerT2V: A Unified Multi-Layer Video Generation Framework
272. ICML 2026Learning a Generative Meta-Model of LLM Activations
273. ICML 2026Learning Coherent Representations: A Topological Approach to Interpretability
274. ICML 2026Learning Discrete Diffusion on Graphs via Free-Energy Gradient Flows
275. ICML 2026Learning Manifold Data with Flow Matching
276. ICML 2026Learning Permutation Distributions via Reflected Diffusion on Ranks
277. ICML 2026Learning to Remember, Learn, and Forget in Attention-Based Models
278. ICML 2026Learning to Watermark in the Latent Space of Generative Models
279. ICML 2026Learning-to-Optimize via Deep Unfolded Flows
280. ICML 2026LEGO-FL: Learning Heterogeneous Federated Models as a LEGO Assembly Games
281. ICML 2026Less is Enough: Synthesizing Diverse Data in LLM Feature Space with Sparse Autoencoders
282. ICML 2026Let Language Constrain Geometry: Vision–Language Models as Semantic and Spatial Critics for 3D Generation
283. ICML 2026Letting Trajectories Spread: Quality-Preserving Control for Diverse Flow Matching
284. ICML 2026LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection
285. ICML 2026Light Forcing: Accelerating Autoregressive Video Diffusion via Sparse Attention
286. ICML 2026Likelihood Matching for Diffusion Models
287. ICML 2026Likelihood over Estimation: Robust Quadratic Discriminant Analysis for Heavy-Tailed Distributions with Theory and Evidence
288. ICML 2026LineageFlow: Flow Matching for High-Fidelity Family-Aware Protein Sequence Generation
289. ICML 2026LipoPU: Pocket-level Prediction of Lipid-Protein Interactions via Positive-Unlabeled Learning
290. ICML 2026LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution
291. ICML 2026Local Mechanisms of Compositional Generalization in Conditional Diffusion
292. ICML 2026Localizing Memorized Regions in Diffusion Models via Coordinate-Wise Curvature Differences
293. ICML 2026Locally Coherent Parallel Decoding in Diffusion Language Models
294. ICML 2026Logical Guidance for the Exact Composition of Diffusion Models
295. ICML 2026LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning
296. ICML 2026Lookahead Path Likelihood Optimization for Diffusion LLMs
297. ICML 2026Lookahead Sample Reward Guidance for Test-Time Scaling of Diffusion Models
298. ICML 2026Lookahead Unmasking Elicits Reliable Decoding in Diffusion Language Models
299. ICML 2026LUCID: Attention with Preconditioned Representations
300. ICML 2026LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Experts

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.