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

527 papers, page 8 of 11

351. NeurIPS 2024SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams
352. NeurIPS 2024Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks
353. NeurIPS 2024Supervised Kernel Thinning
354. NeurIPS 2024TAIA: Large Language Models are Out-of-Distribution Data Learners
355. NeurIPS 2024The Benefits of Balance: From Information Projections to Variance Reduction
356. NeurIPS 2024Theoretical Analysis of Weak-to-Strong Generalization
357. NeurIPS 2024Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution
358. NeurIPS 2024Towards a theory of how the structure of language is acquired by deep neural networks
359. NeurIPS 2024Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking
360. NeurIPS 2024Uncovering the Redundancy in Graph Self-supervised Learning Models
361. NeurIPS 2024Understanding the Gains from Repeated Self-Distillation
362. NeurIPS 2024Understanding the Role of Equivariance in Self-supervised Learning
363. NeurIPS 2024Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs
364. NeurIPS 2024Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis
365. NeurIPS 2024Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning
366. NeurIPS 2024Where does In-context Learning Happen in Large Language Models?
367. NeurIPS 2024You Don’t Need Domain-Specific Data Augmentations When Scaling Self-Supervised Learning
368. NeurIPS 2023$\texttt{TACO}$: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
369. NeurIPS 2023A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
370. NeurIPS 2023A Partially-Supervised Reinforcement Learning Framework for Visual Active Search
371. NeurIPS 2023A polar prediction model for learning to represent visual transformations
372. NeurIPS 2023A Unified Approach to Count-Based Weakly Supervised Learning
373. NeurIPS 2023AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking
374. NeurIPS 2023Alignment with human representations supports robust few-shot learning
375. NeurIPS 2023ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning
376. NeurIPS 2023An Information Theory Perspective on Variance-Invariance-Covariance Regularization
377. NeurIPS 2023An Iterative Self-Learning Framework for Medical Domain Generalization
378. NeurIPS 2023Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods
379. NeurIPS 2023Augmentation-Aware Self-Supervision for Data-Efficient GAN Training
380. NeurIPS 2023BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis
381. NeurIPS 2023Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
382. NeurIPS 2023Better Correlation and Robustness: A Distribution-Balanced Self-Supervised Learning Framework for Automatic Dialogue Evaluation
383. NeurIPS 2023Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense
384. NeurIPS 2023Binary Classification with Confidence Difference
385. NeurIPS 2023Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback
386. NeurIPS 2023Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
387. NeurIPS 2023Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders
388. NeurIPS 2023CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
389. NeurIPS 2023Can semi-supervised learning use all the data effectively? A lower bound perspective
390. NeurIPS 2023CAPro: Webly Supervised Learning with Cross-modality Aligned Prototypes
391. NeurIPS 2023Characterizing the Impacts of Semi-supervised Learning for Weak Supervision
392. NeurIPS 2023Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
393. NeurIPS 2023Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering
394. NeurIPS 2023Combating Representation Learning Disparity with Geometric Harmonization
395. NeurIPS 2023Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
396. NeurIPS 2023Contextually Affinitive Neighborhood Refinery for Deep Clustering
397. NeurIPS 2023Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series
398. NeurIPS 2023Convolutional Visual Prompt for Robust Visual Perception
399. NeurIPS 2023Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry
400. NeurIPS 2023CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoders

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.