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

472 papers, page 5 of 10

201. ICLR 2024MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training
202. ICLR 2024Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning
203. ICLR 2024Modulate Your Spectrum in Self-Supervised Learning
204. ICLR 2024MogaNet: Multi-order Gated Aggregation Network
205. ICLR 2024MOTOR: A Time-to-Event Foundation Model For Structured Medical Records
206. ICLR 2024Multi-resolution HuBERT: Multi-resolution Speech Self-Supervised Learning with Masked Unit Prediction
207. ICLR 2024Multilinear Operator Networks
208. ICLR 2024Multiscale Positive-Unlabeled Detection of AI-Generated Texts
209. ICLR 2024Neural Fourier Transform: A General Approach to Equivariant Representation Learning
210. ICLR 2024Neural Language of Thought Models
211. ICLR 2024Neural Spectral Methods: Self-supervised learning in the spectral domain
212. ICLR 2024Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors
213. ICLR 2024Non-negative Contrastive Learning
214. ICLR 2024Object centric architectures enable efficient causal representation learning
215. ICLR 2024On Harmonizing Implicit Subpopulations
216. ICLR 2024On the Role of Discrete Tokenization in Visual Representation Learning
217. ICLR 2024On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
218. ICLR 2024One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention
219. ICLR 2024Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling
220. ICLR 2024Out-of-Distribution Detection with Negative Prompts
221. ICLR 2024Out-Of-Domain Unlabeled Data Improves Generalization
222. ICLR 2024P$^2$OT: Progressive Partial Optimal Transport for Deep Imbalanced Clustering
223. ICLR 2024P2Seg: Pointly-supervised Segmentation via Mutual Distillation
224. ICLR 2024Parametric Augmentation for Time Series Contrastive Learning
225. ICLR 2024Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution
226. ICLR 2024Perceptual Group Tokenizer: Building Perception with Iterative Grouping
227. ICLR 2024Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model
228. ICLR 2024Point2SSM: Learning Morphological Variations of Anatomies from Point Clouds
229. ICLR 2024Poly-View Contrastive Learning
230. ICLR 2024PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters
231. ICLR 2024Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning
232. ICLR 2024Pre-training with Random Orthogonal Projection Image Modeling
233. ICLR 2024Predicting Emergent Abilities with Infinite Resolution Evaluation
234. ICLR 2024Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization
235. ICLR 2024Protein-ligand binding representation learning from fine-grained interactions
236. ICLR 2024PTaRL: Prototype-based Tabular Representation Learning via Space Calibration
237. ICLR 2024R-MAE: Regions Meet Masked Autoencoders
238. ICLR 2024Real-Fake: Effective Training Data Synthesis Through Distribution Matching
239. ICLR 2024Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments
240. ICLR 2024REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning
241. ICLR 2024ReLoRA: High-Rank Training Through Low-Rank Updates
242. ICLR 2024ReMasker: Imputing Tabular Data with Masked Autoencoding
243. ICLR 2024Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks
244. ICLR 2024Rethinking the Uniformity Metric in Self-Supervised Learning
245. ICLR 2024Retrieval-based Disentangled Representation Learning with Natural Language Supervision
246. ICLR 2024RingAttention with Blockwise Transformers for Near-Infinite Context
247. ICLR 2024Robust Classification via Regression for Learning with Noisy Labels
248. ICLR 2024Robust Similarity Learning with Difference Alignment Regularization
249. ICLR 2024Rotation Has Two Sides: Evaluating Data Augmentation for Deep One-class Classification
250. ICLR 2024SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation

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.