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

1,714 papers, page 18 of 35

851. NeurIPS 2024Retrieval-Augmented Diffusion Models for Time Series Forecasting
852. NeurIPS 2024Return of Unconditional Generation: A Self-supervised Representation Generation Method
853. NeurIPS 2024Right this way: Can VLMs Guide Us to See More to Answer Questions?
854. NeurIPS 2024RoleAgent: Building, Interacting, and Benchmarking High-quality Role-Playing Agents from Scripts
855. NeurIPS 2024S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity
856. NeurIPS 2024Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits
857. NeurIPS 2024Scene Graph Disentanglement and Composition for Generalizable Complex Image Generation
858. NeurIPS 2024Score-based generative models are provably robust: an uncertainty quantification perspective
859. NeurIPS 2024SCube: Instant Large-Scale Scene Reconstruction using VoxSplats
860. NeurIPS 2024SEA: State-Exchange Attention for High-Fidelity Physics Based Transformers
861. NeurIPS 2024Search for Efficient Large Language Models
862. NeurIPS 2024Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment
863. NeurIPS 2024Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences
864. NeurIPS 2024Self-Labeling the Job Shop Scheduling Problem
865. NeurIPS 2024Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation
866. NeurIPS 2024Self-playing Adversarial Language Game Enhances LLM Reasoning
867. NeurIPS 2024SelfCodeAlign: Self-Alignment for Code Generation
868. NeurIPS 2024SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning
869. NeurIPS 2024Sequoia: Scalable and Robust Speculative Decoding
870. NeurIPS 2024Simple and Effective Masked Diffusion Language Models
871. NeurIPS 2024Simple and Fast Distillation of Diffusion Models
872. NeurIPS 2024Simplified and Generalized Masked Diffusion for Discrete Data
873. NeurIPS 2024Skinned Motion Retargeting with Dense Geometric Interaction Perception
874. NeurIPS 2024SMART: Scalable Multi-agent Real-time Motion Generation via Next-token Prediction
875. NeurIPS 2024Soft ascent-descent as a stable and flexible alternative to flooding
876. NeurIPS 2024Sparse Bayesian Generative Modeling for Compressive Sensing
877. NeurIPS 2024Sparse High Rank Adapters
878. NeurIPS 2024Sparse-view Pose Estimation and Reconstruction via Analysis by Generative Synthesis
879. NeurIPS 2024SpatialRGPT: Grounded Spatial Reasoning in Vision-Language Models
880. NeurIPS 2024Stability and Generalizability in SDE Diffusion Models with Measure-Preserving Dynamics
881. NeurIPS 2024Stability and Generalization of Asynchronous SGD: Sharper Bounds Beyond Lipschitz and Smoothness
882. NeurIPS 2024Stabilize the Latent Space for Image Autoregressive Modeling: A Unified Perspective
883. NeurIPS 2024Statistical and Geometrical properties of the Kernel Kullback-Leibler divergence
884. NeurIPS 2024Statistical Efficiency of Distributional Temporal Difference Learning
885. NeurIPS 2024Structured Multi-Track Accompaniment Arrangement via Style Prior Modelling
886. NeurIPS 2024Studying How to Efficiently and Effectively Guide Models with Explanations - A Reproducibility Study
887. NeurIPS 2024Superposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass
888. NeurIPS 2024SyncTweedies: A General Generative Framework Based on Synchronized Diffusions
889. NeurIPS 2024Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models
890. NeurIPS 2024Tactile DreamFusion: Exploiting Tactile Sensing for 3D Generation
891. NeurIPS 2024Taming Generative Diffusion Prior for Universal Blind Image Restoration
892. NeurIPS 2024Task Confusion and Catastrophic Forgetting in Class-Incremental Learning: A Mathematical Framework for Discriminative and Generative Modelings
893. NeurIPS 2024Tetrahedron Splatting for 3D Generation
894. NeurIPS 2024The Closeness of In-Context Learning and Weight Shifting for Softmax Regression
895. NeurIPS 2024The GAN is dead; long live the GAN! A Modern GAN Baseline
896. NeurIPS 2024The tree autoencoder model, with application to hierarchical data visualization
897. NeurIPS 2024Theoretical guarantees in KL for Diffusion Flow Matching
898. NeurIPS 2024Thought of Search: Planning with Language Models Through The Lens of Efficiency
899. NeurIPS 2024Time-Reversal Provides Unsupervised Feedback to LLMs
900. NeurIPS 2024Towards a Scalable Reference-Free Evaluation of Generative 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.