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

41 papers, page 1 of 1

1. ICML 2023A Closer Look at Self-Supervised Lightweight Vision Transformers
2. ICML 2023A Model-free Closeness-of-influence Test for Features in Supervised Learning
3. ICML 2023Contrastive Learning Meets Homophily: Two Birds with One Stone
4. ICML 2023CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations
5. ICML 2023Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least
6. ICML 2023Dink-Net: Neural Clustering on Large Graphs
7. ICML 2023Distance Weighted Supervised Learning for Offline Interaction Data
8. ICML 2023Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language
9. ICML 2023EM-Network: Oracle Guided Self-distillation for Sequence Learning
10. ICML 2023Evaluating Self-Supervised Learning via Risk Decomposition
11. ICML 2023Few-Sample Feature Selection via Feature Manifold Learning
12. ICML 2023Improving Visual Prompt Tuning for Self-supervised Vision Transformers
13. ICML 2023LeadFL: Client Self-Defense against Model Poisoning in Federated Learning
14. ICML 2023Learning Instance-Specific Augmentations by Capturing Local Invariances
15. ICML 2023Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs
16. ICML 2023Loss Balancing for Fair Supervised Learning
17. ICML 2023Mimetic Initialization of Self-Attention Layers
18. ICML 2023Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization
19. ICML 2023NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation
20. ICML 2023On the Stepwise Nature of Self-Supervised Learning
21. ICML 2023On Uni-Modal Feature Learning in Supervised Multi-Modal Learning
22. ICML 2023Random Teachers are Good Teachers
23. ICML 2023RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank
24. ICML 2023Recasting Self-Attention with Holographic Reduced Representations
25. ICML 2023Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction
26. ICML 2023Self-Interpretable Time Series Prediction with Counterfactual Explanations
27. ICML 2023Self-supervised learning of Split Invariant Equivariant representations
28. ICML 2023Self-supervised Neural Factor Analysis for Disentangling Utterance-level Speech Representations
29. ICML 2023Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series
30. ICML 2023Simplified Temporal Consistency Reinforcement Learning
31. ICML 2023SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series
32. ICML 2023Stabilizing Transformer Training by Preventing Attention Entropy Collapse
33. ICML 2023Supervised Metric Learning to Rank for Retrieval via Contextual Similarity Optimization
34. ICML 2023The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning
35. ICML 2023Tied-Augment: Controlling Representation Similarity Improves Data Augmentation
36. ICML 2023Towards Unbiased Training in Federated Open-world Semi-supervised Learning
37. ICML 2023Understanding Self-Distillation in the Presence of Label Noise
38. ICML 2023Understanding Self-Predictive Learning for Reinforcement Learning
39. ICML 2023Weakly Supervised Disentangled Generative Causal Representation Learning
40. ICML 2023Weakly Supervised Regression with Interval Targets
41. ICML 2023Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?

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.