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 12 of 17

551. ICLR 2025TopoDiffusionNet: A Topology-aware Diffusion Model
552. ICLR 2025Topological Schrödinger Bridge Matching
553. ICLR 2025Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers
554. ICLR 2025Towards Hierarchical Rectified Flow
555. ICLR 2025Towards Improving Exploration through Sibling Augmented GFlowNets
556. ICLR 2025Towards Principled Evaluations of Sparse Autoencoders for Interpretability and Control
557. ICLR 2025Towards Scalable Topological Regularizers
558. ICLR 2025Towards Universality: Studying Mechanistic Similarity Across Language Model Architectures
559. ICLR 2025Tracing Representation Progression: Analyzing and Enhancing Layer-Wise Similarity
560. ICLR 2025Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context
561. ICLR 2025Training Free Exponential Context Extension via Cascading KV Cache
562. ICLR 2025Triples as the Key: Structuring Makes Decomposition and Verification Easier in LLM-based TableQA
563. ICLR 2025Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups
564. ICLR 2025Truncated Consistency Models
565. ICLR 2025U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models
566. ICLR 2025Unbounded: A Generative Infinite Game of Character Life Simulation
567. ICLR 2025Unified Convergence Analysis for Score-Based Diffusion Models with Deterministic Samplers
568. ICLR 2025UniGEM: A Unified Approach to Generation and Property Prediction for Molecules
569. ICLR 2025Universal generalization guarantees for Wasserstein distributionally robust models
570. ICLR 2025Unlocking Guidance for Discrete State-Space Diffusion and Flow Models
571. ICLR 2025Unlocking Point Processes through Point Set Diffusion
572. ICLR 2025Variational Search Distributions
573. ICLR 2025VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis
574. ICLR 2025What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models
575. ICLR 2025Where Am I and What Will I See: An Auto-Regressive Model for Spatial Localization and View Prediction
576. ICLR 2025Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers
577. ICLR 2025WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Models
578. ICLR 2025World Model on Million-Length Video And Language With Blockwise RingAttention
579. ICLR 2024$\alpha$TC-VAE: On the relationship between Disentanglement and Diversity
580. ICLR 2024$\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
581. ICLR 2024$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
582. ICLR 2024A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality
583. ICLR 2024A Simple and Scalable Representation for Graph Generation
584. ICLR 2024A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data
585. ICLR 2024A Variational Perspective on Solving Inverse Problems with Diffusion Models
586. ICLR 2024AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
587. ICLR 2024AlpaGasus: Training a Better Alpaca with Fewer Data
588. ICLR 2024Amortizing intractable inference in large language models
589. ICLR 2024Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity
590. ICLR 2024Analyzing and Improving Optimal-Transport-based Adversarial Networks
591. ICLR 2024Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations
592. ICLR 2024Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
593. ICLR 2024BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference
594. ICLR 2024Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
595. ICLR 2024Bellman Optimal Stepsize Straightening of Flow-Matching Models
596. ICLR 2024Bespoke Solvers for Generative Flow Models
597. ICLR 2024Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
598. ICLR 2024Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models
599. ICLR 2024CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling
600. ICLR 2024Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis

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.