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 13 of 27

601. ICML 2026Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
602. ICML 2026XSpecMesh: Quality-Preserving Auto-Regressive Mesh Generation Acceleration via Multi-Head Speculative Decoding
603. ICML 2026You Can Learn Tokenization End-to-End with Reinforcement Learning
604. ICML 2026You Don’t Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models
605. ICML 2025A First-order Generative Bilevel Optimization Framework for Diffusion Models
606. ICML 2025A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
607. ICML 2025A Non-Asymptotic Convergent Analysis for Scored-Based Graph Generative Model via a System of Stochastic Differential Equations
608. ICML 2025A Theory for Conditional Generative Modeling on Multiple Data Sources
609. ICML 2025A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regression
610. ICML 2025A Variational Framework for Improving Naturalness in Generative Spoken Language Models
611. ICML 2025A Variational Perspective on Generative Protein Fitness Optimization
612. ICML 2025Accelerated Diffusion Models via Speculative Sampling
613. ICML 2025ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation
614. ICML 2025AdvI2I: Adversarial Image Attack on Image-to-Image Diffusion Models
615. ICML 2025Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
616. ICML 2025An All-Atom Generative Model for Designing Protein Complexes
617. ICML 2025An Online Learning Approach to Prompt-based Selection of Generative Models and LLMs
618. ICML 2025Analytical Lyapunov Function Discovery: An RL-based Generative Approach
619. ICML 2025Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
620. ICML 2025Angle Domain Guidance: Latent Diffusion Requires Rotation Rather Than Extrapolation
621. ICML 2025Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions
622. ICML 2025Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
623. ICML 2025AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration
624. ICML 2025Autoencoder-Based Hybrid Replay for Class-Incremental Learning
625. ICML 2025AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders
626. ICML 2025Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
627. ICML 2025Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders
628. ICML 2025Benign Overfitting in Token Selection of Attention Mechanism
629. ICML 2025Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance
630. ICML 2025Beyond Task-Specific Reasoning: A Unified Conditional Generative Framework for Abstract Visual Reasoning
631. ICML 2025BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models
632. ICML 2025Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
633. ICML 2025Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images?
634. ICML 2025CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual Learning
635. ICML 2025Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics
636. ICML 2025Categorical Schrödinger Bridge Matching
637. ICML 2025Censor Dependent Variational Inference
638. ICML 2025CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation
639. ICML 2025COExpander: Adaptive Solution Expansion for Combinatorial Optimization
640. ICML 2025Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
641. ICML 2025Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training
642. ICML 2025Compositional Condition Question Answering in Tabular Understanding
643. ICML 2025Compositional Scene Understanding through Inverse Generative Modeling
644. ICML 2025Compressed Image Generation with Denoising Diffusion Codebook Models
645. ICML 2025Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders
646. ICML 2025Concept Reachability in Diffusion Models: Beyond Dataset Constraints
647. ICML 2025Concept-Centric Token Interpretation for Vector-Quantized Generative Models
648. ICML 2025ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
649. ICML 2025Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
650. ICML 2025Continuous Semi-Implicit Models

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.