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 52 of 87

2551. ICLR 2024Multi-Source Diffusion Models for Simultaneous Music Generation and Separation
2552. ICLR 2024Multimarginal Generative Modeling with Stochastic Interpolants
2553. ICLR 2024Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
2554. ICLR 2024NEFTune: Noisy Embeddings Improve Instruction Finetuning
2555. ICLR 2024Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
2556. ICLR 2024Neural Optimal Transport with General Cost Functionals
2557. ICLR 2024Neural structure learning with stochastic differential equations
2558. ICLR 2024Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data
2559. ICLR 2024Noise-free Score Distillation
2560. ICLR 2024OctoPack: Instruction Tuning Code Large Language Models
2561. ICLR 2024On Error Propagation of Diffusion Models
2562. ICLR 2024On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
2563. ICLR 2024On the Foundations of Shortcut Learning
2564. ICLR 2024On the Reliability of Watermarks for Large Language Models
2565. ICLR 2024On the Stability of Iterative Retraining of Generative Models on their own Data
2566. ICLR 2024PhyloGFN: Phylogenetic inference with generative flow networks
2567. ICLR 2024Pre-Training and Fine-Tuning Generative Flow Networks
2568. ICLR 2024Provable Compositional Generalization for Object-Centric Learning
2569. ICLR 2024Quality-Diversity through AI Feedback
2570. ICLR 2024R-MAE: Regions Meet Masked Autoencoders
2571. ICLR 2024Raidar: geneRative AI Detection viA Rewriting
2572. ICLR 2024Relay Diffusion: Unifying diffusion process across resolutions for image synthesis
2573. ICLR 2024Revisit and Outstrip Entity Alignment: A Perspective of Generative Models
2574. ICLR 2024Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
2575. ICLR 2024SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
2576. ICLR 2024Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
2577. ICLR 2024SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
2578. ICLR 2024Scale-Adaptive Diffusion Model for Complex Sketch Synthesis
2579. ICLR 2024Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions
2580. ICLR 2024SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
2581. ICLR 2024SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction
2582. ICLR 2024Self-Alignment with Instruction Backtranslation
2583. ICLR 2024Self-Consuming Generative Models Go MAD
2584. ICLR 2024Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning
2585. ICLR 2024Separate and Diffuse: Using a Pretrained Diffusion Model for Better Source Separation
2586. ICLR 2024SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking
2587. ICLR 2024Single Motion Diffusion
2588. ICLR 2024SliceGPT: Compress Large Language Models by Deleting Rows and Columns
2589. ICLR 2024Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community
2590. ICLR 2024Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models
2591. ICLR 2024Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
2592. ICLR 2024Sparse Autoencoders Find Highly Interpretable Features in Language Models
2593. ICLR 2024STREAM: Spatio-TempoRal Evaluation and Analysis Metric for Video Generative Models
2594. ICLR 2024Talk like a Graph: Encoding Graphs for Large Language Models
2595. ICLR 2024TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
2596. ICLR 2024The Generative AI Paradox: “What It Can Create, It May Not Understand”
2597. ICLR 2024Towards Generative Abstract Reasoning: Completing Raven’s Progressive Matrix via Rule Abstraction and Selection
2598. ICLR 2024Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation
2599. ICLR 2024Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models
2600. ICLR 2024Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond

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.