Deep learning · self supervised learning papers, 2023–2026

Key findings

• Deep learning · self supervised learning went from 455 papers in 2023 to 534 in 2026, roughly 1.2x in three years.
• ICLR publishes the most Deep learning · self supervised learning work: 693 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with General ML · unsupervised and semisupervised learning: papers tagged with both rose from 23 in 2023 to 86 in 2026.
• Among the 11 topics under Deep Learning, it ranks #4 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 2026Attending on Attention ($A^2$): Smaller Self-Supervised ViTs Localize Better Than Larger Ones
• ICML 20263D-DLP: Self-supervised 3D Object-centric Scene Representation Learning
• ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
• CVPR 2026A Stitch in Time Learning Procedural Workflow via Self-Supervised Plackett-Luce
• NeurIPS 2025$\textit{HiMaCon:}$ Discovering Hierarchical Manipulation Concepts from Unlabeled Multi-Modal Data
• ICML 2025An Augmentation-Aware Theory for Self-Supervised Contrastive Learning
• ICLR 2025Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding
• CVPR 2025A Unified Framework for Heterogeneous Semi-supervised Learning
• NeurIPS 2024Intrinsic Self-Supervision for Data Quality Audits
• ICML 2024Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
• ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
• CVPR 2024Exploring Efficient Asymmetric Blind-Spots for Self-Supervised Denoising in Real-World Scenarios
• NeurIPS 2023A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
• ICML 2023A Closer Look at Self-Supervised Lightweight Vision Transformers
• ICLR 2023A Multi-Grained Self-Interpretable Symbolic-Neural Model For Single/Multi-Labeled Text Classification
• CVPR 2023Are Data-Driven Explanations Robust Against Out-of-Distribution Data?
• NeurIPS 2026AudioSphere: Towards Self-Supervised Spatial Audio Representation Models
• ICML 20263DPoV: Improving 3D understanding via Patch Ordering on Videos
• ICLR 2026Angle K-Means
• CVPR 2026Action Motifs Self-Supervised Hierarchical Representation of Human Body Movements

All Deep learning · self supervised learning papers

195 papers, page 1 of 4

1. ICLR 2026A Bayesian Nonparametric Framework For Learning Disentangled Representations
2. ICLR 2026A Federated Generalized Expectation-Maximization Algorithm for Mixture Models with an Unknown Number of Components
3. ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
4. ICLR 2026Accessible, Realistic, and Fair Evaluation of Positive-Unlabeled Learning Algorithms
5. ICLR 2026Adapting Self-Supervised Representations as a Latent Space for Efficient Generation
6. ICLR 2026Adaptive Conformal Prediction via Mixture-of-Experts Gating Similarity
7. ICLR 2026Adaptive Width Neural Networks
8. ICLR 2026Advancing End-to-End Pixel-Space Generative Modeling via Self-Supervised Pre-Training
9. ICLR 2026Agentic Context Engineering: Learning Comprehensive Contexts for Self-Improving Language Models
10. ICLR 2026An Efficient SE(p)-Invariant Transport Metric Driven by Polar Transport Discrepancy-based Representation
11. ICLR 2026Anchored Supervised Fine-Tuning
12. ICLR 2026Angle K-Means
13. ICLR 2026Animal behavioral analysis and neural encoding with transformer-based self-supervised pretraining
14. ICLR 2026AnyUp: Universal Feature Upsampling
15. ICLR 2026AP-OOD: Attention Pooling for Out-of- Distribution Detection
16. ICLR 2026Behavioral Embeddings of Programs: A Quasi-Dynamic Approach for Optimization Prediction
17. ICLR 2026BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training
18. ICLR 2026Better Together: Leveraging Unpaired Multimodal Data for Stronger Unimodal Models
19. ICLR 2026Beyond Entity Correlations: Disentangling Event Causal Puzzles in Temporal Knowledge Graphs
20. ICLR 2026Bi-Lipschitz Autoencoder With Injectivity Guarantee
21. ICLR 2026BioTamperNet: Affinity-Guided State-Space Model Detecting Tampered Biomedical Images
22. ICLR 2026Boosting Open Set Recognition Performance through Modulated Representation Learning
23. ICLR 2026Brain-Semantoks: Learning Semantic Tokens of Brain Dynamics with a Self-Distilled Foundation Model
24. ICLR 2026Breaking Gradient Temporal Collinearity for Robust Spiking Neural Networks
25. ICLR 2026Calibrating Verbalized Confidence with Self-Generated Distractors
26. ICLR 2026CARL: Camera-Agnostic Representation Learning for Spectral Image Analysis
27. ICLR 2026Catching the Details: Self-Distilled RoI Predictors for Fine-Grained MLLM Perception
28. ICLR 2026CHAMMI-75: pre-training multi-channel models with heterogeneous microscopy images
29. ICLR 2026Co-rewarding: Stable Self-supervised RL for Eliciting Reasoning in Large Language Models
30. ICLR 2026CoLA: Co-Calibrated Logit Adjustment for Long-Tailed Semi-Supervised Learning
31. ICLR 2026Command-V: Training-Free Representation Finetuning Transfer
32. ICLR 2026Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification
33. ICLR 2026ConRep4CO: Contrastive Representation Learning of Combinatorial Optimization Instances across Types
34. ICLR 2026Contrastive Predictive Coding Done Right for Mutual Information Estimation
35. ICLR 2026COSMO-INR: Complex Sinusoidal Modulation for Implicit Neural Representations
36. ICLR 2026CroCoDiLight: Repurposing Cross-View Completion Encoders for Relighting
37. ICLR 2026CryoLVM: Self-supervised Learning from Cryo-EM Density Maps with Large Vision Models
38. ICLR 2026CSRv2: Unlocking Ultra-Sparse Embeddings
39. ICLR 2026Curse of Slicing: Why Sliced Mutual Information is a Deceptive Measure of Statistical Dependence
40. ICLR 2026Cutting the Skip: Training Residual-Free Transformers
41. ICLR 2026Darwin Gödel Machine: Open-Ended Evolution of Self-Improving Agents
42. ICLR 2026Decoding Dynamic Visual Experience from Calcium Imaging via Cell-Pattern-Aware SSL
43. ICLR 2026Decomposition of Concept-Level Rules in Visual Scenes
44. ICLR 2026Decoupling Dynamical Richness from Representation Learning: Towards Practical Measurement
45. ICLR 2026Deep Learning with Learnable Product-Structured Activations
46. ICLR 2026Difference Predictive Coding for Training Spiking Neural Networks
47. ICLR 2026Differentiable JPEG-based Input Perturbation for Knowledge Distillation Amplification via Conditional Mutual Information Maximization
48. ICLR 2026Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective
49. ICLR 2026DiVeQ: Differentiable Vector Quantization Using the Reparameterization Trick
50. ICLR 2026Divergence-Free Neural Networks with Application to Image Denoising

FAQ

How many Deep learning · self supervised learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,958 in total: 455 in 2023, 472 in 2024, 497 in 2025, 534 in 2026.

How many Deep learning · self supervised learning papers are at NeurIPS 2026?

NeurIPS 2026 has 110 Deep learning · self supervised learning papers, versus 147 the year before.

How many Deep learning · self supervised learning papers are at ICLR 2026?

ICLR 2026 has 195 Deep learning · self supervised learning papers, versus 195 the year before.

How many Deep learning · self supervised learning papers are at ICML 2026?

ICML 2026 has 135 Deep learning · self supervised learning papers, versus 72 the year before.

How many Deep learning · self supervised learning papers are at CVPR 2026?

CVPR 2026 has 94 Deep learning · self supervised learning papers, versus 83 the year before.

Which conference publishes the most Deep learning · self supervised learning papers?

ICLR, with 693 papers from 2023 to 2026.