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 13 of 35

601. NeurIPS 2024A Theoretical Understanding of Self-Correction through In-context Alignment
602. NeurIPS 2024A versatile informative diffusion model for single-cell ATAC-seq data generation and analysis
603. NeurIPS 2024Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences
604. NeurIPS 2024ACES: Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
605. NeurIPS 2024Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
606. NeurIPS 2024Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
607. NeurIPS 2024Adversarial Schrödinger Bridge Matching
608. NeurIPS 2024AFBench: A Large-scale Benchmark for Airfoil Design
609. NeurIPS 2024AirSketch: Generative Motion to Sketch
610. NeurIPS 2024Aligning Diffusion Models by Optimizing Human Utility
611. NeurIPS 2024An Equivalence Between Static and Dynamic Regret Minimization
612. NeurIPS 2024An Image is Worth 32 Tokens for Reconstruction and Generation
613. NeurIPS 2024Animate3D: Animating Any 3D Model with Multi-view Video Diffusion
614. NeurIPS 2024Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models
615. NeurIPS 2024Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting
616. NeurIPS 2024Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems
617. NeurIPS 2024ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction
618. NeurIPS 2024Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication
619. NeurIPS 2024Autoregressive Image Generation without Vector Quantization
620. NeurIPS 2024Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs
621. NeurIPS 2024Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
622. NeurIPS 2024Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming
623. NeurIPS 2024BERTs are Generative In-Context Learners
624. NeurIPS 2024Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps
625. NeurIPS 2024BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling
626. NeurIPS 2024Boosting Alignment for Post-Unlearning Text-to-Image Generative Models
627. NeurIPS 2024BrainBits: How Much of the Brain are Generative Reconstruction Methods Using?
628. NeurIPS 2024Bridging Geometric States via Geometric Diffusion Bridge
629. NeurIPS 2024Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models
630. NeurIPS 2024Bridging OOD Detection and Generalization: A Graph-Theoretic View
631. NeurIPS 2024C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory
632. NeurIPS 2024Can Models Learn Skill Composition from Examples?
633. NeurIPS 2024Cascade of phase transitions in the training of energy-based models
634. NeurIPS 2024Categorical Flow Matching on Statistical Manifolds
635. NeurIPS 2024Causal language modeling can elicit search and reasoning capabilities on logic puzzles
636. NeurIPS 2024Challenges of Generating Structurally Diverse Graphs
637. NeurIPS 2024Classification Diffusion Models: Revitalizing Density Ratio Estimation
638. NeurIPS 2024ClavaDDPM: Multi-relational Data Synthesis with Cluster-guided Diffusion Models
639. NeurIPS 2024Compositional 3D-aware Video Generation with LLM Director
640. NeurIPS 2024Conditioning non-linear and infinite-dimensional diffusion processes
641. NeurIPS 2024Consistency of Neural Causal Partial Identification
642. NeurIPS 2024Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
643. NeurIPS 2024Contrastive-Equivariant Self-Supervised Learning Improves Alignment with Primate Visual Area IT
644. NeurIPS 2024ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language Models
645. NeurIPS 2024COSMIC: Compress Satellite Image Efficiently via Diffusion Compensation
646. NeurIPS 2024CRAG - Comprehensive RAG Benchmark
647. NeurIPS 2024Credit Attribution and Stable Compression
648. NeurIPS 2024CryoBench: Datasets and Benchmarks for Heterogeneous Cryo-EM Reconstruction
649. NeurIPS 2024CryoGEM: Physics-Informed Generative Cryo-Electron Microscopy
650. NeurIPS 2024Cryptographic Hardness of Score Estimation

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.