Deep learning · self supervised learning papers, 2023–2026
Deep learning area: self_supervised_learning
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 1,958 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 160 | 108 | 41 | 146 | 455 |
| 2024 | 110 | 195 | 62 | 105 | 472 |
| 2025 | 147 | 195 | 72 | 83 | 497 |
| 2026 | 110 | 195 | 135 | 94 | 534 |
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
160 papers, page 1 of 4
- NeurIPS 2023$\texttt{TACO}$: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
- NeurIPS 2023A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
- NeurIPS 2023A Partially-Supervised Reinforcement Learning Framework for Visual Active Search
- NeurIPS 2023A polar prediction model for learning to represent visual transformations
- NeurIPS 2023A Unified Approach to Count-Based Weakly Supervised Learning
- NeurIPS 2023AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking
- NeurIPS 2023Alignment with human representations supports robust few-shot learning
- NeurIPS 2023ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning
- NeurIPS 2023An Information Theory Perspective on Variance-Invariance-Covariance Regularization
- NeurIPS 2023An Iterative Self-Learning Framework for Medical Domain Generalization
- NeurIPS 2023Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods
- NeurIPS 2023Augmentation-Aware Self-Supervision for Data-Efficient GAN Training
- NeurIPS 2023BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis
- NeurIPS 2023Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
- NeurIPS 2023Better Correlation and Robustness: A Distribution-Balanced Self-Supervised Learning Framework for Automatic Dialogue Evaluation
- NeurIPS 2023Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense
- NeurIPS 2023Binary Classification with Confidence Difference
- NeurIPS 2023Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback
- NeurIPS 2023Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
- NeurIPS 2023Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders
- NeurIPS 2023CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
- NeurIPS 2023Can semi-supervised learning use all the data effectively? A lower bound perspective
- NeurIPS 2023CAPro: Webly Supervised Learning with Cross-modality Aligned Prototypes
- NeurIPS 2023Characterizing the Impacts of Semi-supervised Learning for Weak Supervision
- NeurIPS 2023Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
- NeurIPS 2023Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering
- NeurIPS 2023Combating Representation Learning Disparity with Geometric Harmonization
- NeurIPS 2023Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
- NeurIPS 2023Contextually Affinitive Neighborhood Refinery for Deep Clustering
- NeurIPS 2023Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series
- NeurIPS 2023Convolutional Visual Prompt for Robust Visual Perception
- NeurIPS 2023Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry
- NeurIPS 2023CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoders
- NeurIPS 2023Cross-modal Active Complementary Learning with Self-refining Correspondence
- NeurIPS 2023Cross-Scale MAE: A Tale of Multiscale Exploitation in Remote Sensing
- NeurIPS 2023Curriculum Learning With Infant Egocentric Videos
- NeurIPS 2023DAW: Exploring the Better Weighting Function for Semi-supervised Semantic Segmentation
- NeurIPS 2023Differentiable Clustering with Perturbed Spanning Forests
- NeurIPS 2023Differentiable sorting for censored time-to-event data.
- NeurIPS 2023Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection
- NeurIPS 2023DiffUTE: Universal Text Editing Diffusion Model
- NeurIPS 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction
- NeurIPS 2023DinoSR: Self-Distillation and Online Clustering for Self-supervised Speech Representation Learning
- NeurIPS 2023Disentangling Voice and Content with Self-Supervision for Speaker Recognition
- NeurIPS 2023Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning
- NeurIPS 2023Does Visual Pretraining Help End-to-End Reasoning?
- NeurIPS 2023Doubly-Robust Self-Training
- NeurIPS 2023DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions
- NeurIPS 2023Dual Mean-Teacher: An Unbiased Semi-Supervised Framework for Audio-Visual Source Localization
- NeurIPS 2023Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative MARL
Ask about this trend from Claude or Cursor
Connect the Paperlist MCP and your assistant can pull the numbers on this page while you draft a survey, pick a direction or plan a submission: papers per year and venue, growth, the fastest-rising sub-themes and representative papers, shaped around your question.
Copy this prompt into your assistant
Use paperlist to show how Deep learning · self supervised learning papers grew at ICLR from 2023 to 2026, and which year jumped the most.
Tool the assistant calls: get_topic_stats {"topic": "dl-self-supervised-learning"}
Set up Paperlist MCP in two minutes (Claude Code, Cursor, Codex, ChatGPT)
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.
More in Deep Learning
- Diffusion Models 6,900
- Deep learning · generative models and autoencoders 4,314
- Deep learning · large language models 2,334
- 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