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 20243D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
2. ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
3. ICLR 2024A Mutual Information Perspective on Federated Contrastive Learning
4. ICLR 2024A Recipe for Improved Certifiable Robustness
5. ICLR 2024A representation-learning game for classes of prediction tasks
6. ICLR 2024Accelerated Sampling with Stacked Restricted Boltzmann Machines
7. ICLR 2024An Investigation of Representation and Allocation Harms in Contrastive Learning
8. ICLR 2024Annealing Self-Distillation Rectification Improves Adversarial Training
9. ICLR 2024Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
10. ICLR 2024Attention-based Iterative Decomposition for Tensor Product Representation
11. ICLR 2024AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning
12. ICLR 2024Batch normalization is sufficient for universal function approximation in CNNs
13. ICLR 2024BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation
14. ICLR 2024Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain
15. ICLR 2024Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
16. ICLR 2024Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments
17. ICLR 2024Bridging State and History Representations: Understanding Self-Predictive RL
18. ICLR 2024CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception
19. ICLR 2024Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning
20. ICLR 2024CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting
21. ICLR 2024Cauchy-Schwarz Divergence Information Bottleneck for Regression
22. ICLR 2024Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks
23. ICLR 2024CODE REPRESENTATION LEARNING AT SCALE
24. ICLR 2024Compressing Latent Space via Least Volume
25. ICLR 2024ConR: Contrastive Regularizer for Deep Imbalanced Regression
26. ICLR 2024Consistent Multi-Class Classification from Multiple Unlabeled Datasets
27. ICLR 2024Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation
28. ICLR 2024Contrastive Learning is Spectral Clustering on Similarity Graph
29. ICLR 2024CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping
30. ICLR 2024DAFA: Distance-Aware Fair Adversarial Training
31. ICLR 2024Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data
32. ICLR 2024Deep Orthogonal Hypersphere Compression for Anomaly Detection
33. ICLR 2024Deep Temporal Graph Clustering
34. ICLR 2024Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks
35. ICLR 2024Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
36. ICLR 2024Distinguished In Uniform: Self-Attention Vs. Virtual Nodes
37. ICLR 2024Diving Segmentation Model into Pixels
38. ICLR 2024Do Generated Data Always Help Contrastive Learning?
39. ICLR 2024Does CLIP’s generalization performance mainly stem from high train-test similarity?
40. ICLR 2024Dual-Encoders for Extreme Multi-label Classification
41. ICLR 2024Early Stopping Against Label Noise Without Validation Data
42. ICLR 2024Effective pruning of web-scale datasets based on complexity of concept clusters
43. ICLR 2024Efficient Score Matching with Deep Equilibrium Layers
44. ICLR 2024Enabling Lanuguage Models to Implicitly Learn Self-Improvement
45. ICLR 2024Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction
46. ICLR 2024Exploring Target Representations for Masked Autoencoders
47. ICLR 2024Fast Hyperboloid Decision Tree Algorithms
48. ICLR 2024Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
49. ICLR 2024Feature-aligned N-BEATS with Sinkhorn divergence
50. ICLR 2024FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation

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.