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

830 papers, page 14 of 17

651. ICLR 2024HiGen: Hierarchical Graph Generative Networks
652. ICLR 2024How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models
653. ICLR 2024How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
654. ICLR 2024Human Motion Diffusion as a Generative Prior
655. ICLR 2024Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners
656. ICLR 2024HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
657. ICLR 2024Idempotence and Perceptual Image Compression
658. ICLR 2024Idempotent Generative Network
659. ICLR 2024Improved sampling via learned diffusions
660. ICLR 2024Improved Techniques for Training Consistency Models
661. ICLR 2024In-Context Learning Learns Label Relationships but Is Not Conventional Learning
662. ICLR 2024InfoCon: Concept Discovery with Generative and Discriminative Informativeness
663. ICLR 2024Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models
664. ICLR 2024Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
665. ICLR 2024InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior
666. ICLR 2024JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention
667. ICLR 2024Label-Noise Robust Diffusion Models
668. ICLR 2024Language Model Cascades: Token-Level Uncertainty And Beyond
669. ICLR 2024Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication
670. ICLR 2024Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior
671. ICLR 2024Learning Energy Decompositions for Partial Inference in GFlowNets
672. ICLR 2024Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
673. ICLR 2024Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling
674. ICLR 2024Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency
675. ICLR 2024Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments
676. ICLR 2024Lifting Architectural Constraints of Injective Flows
677. ICLR 2024Light Schrödinger Bridge
678. ICLR 2024Lipschitz Singularities in Diffusion Models
679. ICLR 2024LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses
680. ICLR 2024Localizing and Editing Knowledge In Text-to-Image Generative Models
681. ICLR 2024Long-tailed Diffusion Models with Oriented Calibration
682. ICLR 2024LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
683. ICLR 2024Machine Unlearning for Image-to-Image Generative Models
684. ICLR 2024Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
685. ICLR 2024Manifold Diffusion Fields
686. ICLR 2024Manifold Preserving Guided Diffusion
687. ICLR 2024Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners
688. ICLR 2024MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods
689. ICLR 2024MiniLLM: Knowledge Distillation of Large Language Models
690. ICLR 2024Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
691. ICLR 2024Modelling complex vector drawings with stroke-clouds
692. ICLR 2024Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data
693. ICLR 2024Multi-Source Diffusion Models for Simultaneous Music Generation and Separation
694. ICLR 2024Multimarginal Generative Modeling with Stochastic Interpolants
695. ICLR 2024Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
696. ICLR 2024NEFTune: Noisy Embeddings Improve Instruction Finetuning
697. ICLR 2024Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
698. ICLR 2024Neural Optimal Transport with General Cost Functionals
699. ICLR 2024Neural structure learning with stochastic differential equations
700. ICLR 2024Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data

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.