Deep learning · generative models and autoencoders papers, 2023–2026
Deep learning area: generative_models_and_autoencoders
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 4,314 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 776 | 78 | 286 | 76 | 1,216 |
| 2024 | 349 | 174 | 139 | 106 | 768 |
| 2025 | 240 | 275 | 275 | 110 | 900 |
| 2026 | 349 | 303 | 604 | 174 | 1,430 |
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 11 of 87
- ICML 2026Any-Order GPT as Masked Diffusion Model: Decoupling Formulation and Architecture
- ICML 2026AnyBand-Diff: A Unified Remote Sensing Image Generation and Band Repair Framework with Spectral Priors
- ICML 2026Anytime Safe PAC Efficient Reasoning
- ICML 2026ARC-Decode: Accelerated Decoding with Risk-Bounded Acceptance
- ICML 2026ArcDAE: Asymmetric Rectified Contrastive Diffusion Autoencoder for Unified Representation Learning
- ICML 2026Are First-Order Diffusion Samplers Really Slower? A Fast Forward-Value Approach
- ICML 2026AREA: Attribute Extraction and Aggregation for CLIP-Based Class-Incremental Learning
- ICML 2026ASIR: Steganography for Diffusion Models via Antipodal Sampling and Iterative Recovery
- ICML 2026At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization
- ICML 2026Attacks on Machine-Text Detectors Retain Stylistic Fingerprints
- ICML 2026Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models
- ICML 2026Attention Sparsity is Input-Stable: Training-Free Sparse Attention for Video Generation via Offline Sparsity Profiling and Online QK Co-Clustering
- ICML 2026Automatic Layer Selection for Hallucination Detection
- ICML 2026Autoregression with Self-Token Prediction
- ICML 2026Autoregressive Image Generation with Masked Bit Modeling
- ICML 2026AutoSizer: Automatic Sizing of Analog and Mixed-Signal Circuits via Large Language Model (LLM) Agents
- ICML 2026Balancing Plasticity and Stability with Fast and Slow Successor Features
- ICML 2026Base Models Know How to Reason, Thinking Models Learn When
- ICML 2026Behavioral Mode Discovery for Fine-tuning Multimodal Generative Policies
- ICML 2026Being More Lightweight and Practical: Mini-sized Contrastive Learning Pre-trained Models for Fine-grained Traffic Task
- ICML 2026Benchmarking and Improving Fine-Grained Text-to-Image Alignment via Paired Reinforcement Learning
- ICML 2026Best of Both Worlds: Multimodal Reasoning and Generation via Unified Discrete Flow Matching
- ICML 2026Beyond Generative Priors: Minority Sampling with JEPA-Guided Diffusion
- ICML 2026Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clustering
- ICML 2026Beyond Pixel Histories: World Models with Persistent 3D State
- ICML 2026Beyond Reactivity: Proactive Adaptive Conformal Inference for Online LLM Factuality
- ICML 2026Bi-Anchor Interpolation Solver for Accelerating Generative Modeling
- ICML 2026Biased Generalization in Diffusion Models
- ICML 2026Boosting World Models Learning via Latent-Space Value Alignment
- ICML 2026Breaking the Factorization Barrier in Diffusion Language Models
- ICML 2026Breaking the Lock-in: Diversifying Text-to-Image Generation via Representation Modulation
- ICML 2026Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression
- ICML 2026Breaking the Synthetic-Real Domain Shortcut for Training-Free Generative Replay-based Class Incremental Learning
- ICML 2026BRIDGE: Predicting Human Task Completion Time From Model Performance
- ICML 2026Bridging Functional and Representational Similarity via Usable Information
- ICML 2026Budget-Constrained Step-Level Diffusion Caching
- ICML 2026C$^{2}$R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse Autoencoders
- ICML 2026CacheEdit: Efficient Multi-round Image Editing via Adaptive Token-wise Reuse.
- ICML 2026Calibrated Test-Time Guidance for Bayesian Inference
- ICML 2026Calibrating Generative Models to Distributional Constraints
- ICML 2026CameraNoise: Enabling Faithful Camera Control in Video Diffusion through Geometry-Flow-Guided Noise Warping
- ICML 2026CamGeo: Sparse Camera-Conditioned Image-to-Video Generation with 3D Geometry Priors
- ICML 2026CANDI: Hybrid Discrete-Continuous Diffusion Models
- ICML 2026Capability Traps in DPO
- ICML 2026CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation
- ICML 2026Cascaded Flow Matching for Heterogeneous Tabular Data with Mixed-Type Features
- ICML 2026Categorical Flow Maps
- ICML 2026Categorical Reparameterization with Denoising Diffusion Models
- ICML 2026CatFlow: Co-generation of Slab-Adsorbate Systems via Flow Matching
- ICML 2026Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation
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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.
More in Deep Learning
- Diffusion Models 6,900
- Deep learning · large language models 2,334
- Deep learning · self supervised learning 1,958
- Deep learning · graph neural networks 1,648
- Deep learning · optimization 953
- Deep learning · representation learning 802
- Deep learning · probabilistic methods 637
- Deep learning · foundation models 536
- Deep learning · causal inference 316
- Deep learning · transfer learning 197