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 15 of 17

701. ICLR 2024Noise-free Score Distillation
702. ICLR 2024OctoPack: Instruction Tuning Code Large Language Models
703. ICLR 2024On Error Propagation of Diffusion Models
704. ICLR 2024On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
705. ICLR 2024On the Foundations of Shortcut Learning
706. ICLR 2024On the Reliability of Watermarks for Large Language Models
707. ICLR 2024On the Stability of Iterative Retraining of Generative Models on their own Data
708. ICLR 2024PhyloGFN: Phylogenetic inference with generative flow networks
709. ICLR 2024Pre-Training and Fine-Tuning Generative Flow Networks
710. ICLR 2024Provable Compositional Generalization for Object-Centric Learning
711. ICLR 2024Quality-Diversity through AI Feedback
712. ICLR 2024R-MAE: Regions Meet Masked Autoencoders
713. ICLR 2024Raidar: geneRative AI Detection viA Rewriting
714. ICLR 2024Relay Diffusion: Unifying diffusion process across resolutions for image synthesis
715. ICLR 2024Revisit and Outstrip Entity Alignment: A Perspective of Generative Models
716. ICLR 2024Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
717. ICLR 2024SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
718. ICLR 2024Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
719. ICLR 2024SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
720. ICLR 2024Scale-Adaptive Diffusion Model for Complex Sketch Synthesis
721. ICLR 2024Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions
722. ICLR 2024SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
723. ICLR 2024SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction
724. ICLR 2024Self-Alignment with Instruction Backtranslation
725. ICLR 2024Self-Consuming Generative Models Go MAD
726. ICLR 2024Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning
727. ICLR 2024Separate and Diffuse: Using a Pretrained Diffusion Model for Better Source Separation
728. ICLR 2024SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking
729. ICLR 2024Single Motion Diffusion
730. ICLR 2024SliceGPT: Compress Large Language Models by Deleting Rows and Columns
731. ICLR 2024Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community
732. ICLR 2024Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models
733. ICLR 2024Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
734. ICLR 2024Sparse Autoencoders Find Highly Interpretable Features in Language Models
735. ICLR 2024STREAM: Spatio-TempoRal Evaluation and Analysis Metric for Video Generative Models
736. ICLR 2024Talk like a Graph: Encoding Graphs for Large Language Models
737. ICLR 2024TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
738. ICLR 2024The Generative AI Paradox: “What It Can Create, It May Not Understand”
739. ICLR 2024Towards Generative Abstract Reasoning: Completing Raven’s Progressive Matrix via Rule Abstraction and Selection
740. ICLR 2024Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation
741. ICLR 2024Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models
742. ICLR 2024Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond
743. ICLR 2024Transformer-VQ: Linear-Time Transformers via Vector Quantization
744. ICLR 2024TUVF: Learning Generalizable Texture UV Radiance Fields
745. ICLR 2024Unbiased Watermark for Large Language Models
746. ICLR 2024Understanding the Effects of RLHF on LLM Generalisation and Diversity
747. ICLR 2024Universal Guidance for Diffusion Models
748. ICLR 2024Unveiling and Manipulating Prompt Influence in Large Language Models
749. ICLR 2024Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis
750. ICLR 2024Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency

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.