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

532 papers, page 7 of 11

301. ICML 2026Bio-Inspired Self-Supervised Learning for Wrist-worn Accelerometer Data
302. ICML 2026Breaking the Reference Bottleneck via Learning to Rewrite Conversational Queries without Gold Reference Passages
303. ICML 2026Brep2Shape: Boundary and Shape Representation Alignment via Self-supervised Transformers
304. ICML 2026CalM: A Self-Supervised Foundation Model for Population Dynamics in Calcium Imaging Data
305. ICML 2026Can local learning match self-supervised backpropagation?
306. ICML 2026Causal-JEPA: Learning World Models through Object-Level Latent Masking
307. ICML 2026Certifying Graph Neural Networks Against Label and Structure Poisoning
308. ICML 2026CodeMamba: Shifting from Target Semantics to Self-Supervised Background Manifold Learning for Singularity Detection in Infrared Sequences
309. ICML 2026Contribution Weights: A Geometrical Analysis of Self-Attention Transformers
310. ICML 2026Deriving Neural Scaling Laws from the Statistics of Natural Language
311. ICML 2026DiL: Discrete-anchored Representation Alignment for Semi-Supervised Continual Learning
312. ICML 2026Directional Neural Collapse Explains Few-Shot Transfer in Self-Supervised Learning
313. ICML 2026Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models
314. ICML 2026DisPOSE: Projected Polystochastic Diffusion for Self-Supervised Multi-View 3D Human Pose Estimation
315. ICML 2026DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement
316. ICML 2026Divide and Contrast: Learning Robust Temporal Features without Augmentation
317. ICML 2026DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization
318. ICML 2026Evaluating the Representation Space of Diffusion Models via Self-Supervised Principles
319. ICML 2026FairSSL: Fair Multimodal Self-Supervised Learning
320. ICML 2026Faster Query-Key Learning Sharpens Attention in Self-Attention Models
321. ICML 2026FedSDR: Federated Self-Distillation with Rectification
322. ICML 2026FedVeer: Self-Adaptive Skew Estimation for Robust Federated Learning
323. ICML 2026Fine-Tuning Masked Diffusion for Provable Self-Correction
324. ICML 2026Foresee-to-Ground: From Predictive Temporal Perception to Evidence-Driven Reasoning for Video Temporal Grounding
325. ICML 2026FoundObj: Self-supervised Foundation Models as Rewards for Label-free 3D Object Segmentation
326. ICML 2026From Extrinsic to Intrinsic: Geodesic-Guided Representation Learning for 3D Geometric Data
327. ICML 2026Gauge-Equivariant Graph Networks via Self-Interference Cancellation
328. ICML 2026Generalized Discrete Diffusion with Self-Correction
329. ICML 2026Geometric Collapse: When Vision Models Fail to Verify Physical Causality
330. ICML 2026Geometric Reciprocity: Unlocking Self-Supervision for Stereoscopic Video Generation
331. ICML 2026GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training
332. ICML 2026Global Geometry Is Not Enough for Vision Representations
333. ICML 2026Hierarchical Goal Abstractions via Learned Subset Relations
334. ICML 2026IdEst: Assessing Self-Supervised Learning Representations via Intrinsic Dimension
335. ICML 2026Implicit Actor Critic Coupling via a Supervised Learning Framework for RLVR
336. ICML 2026Improving Diffusion Planners by Self-Supervised Action Gating with Energies
337. ICML 2026Interpretable Self-Supervised Learning via Representer Landmarks and Nyström Approximation
338. ICML 2026Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization
339. ICML 2026Joint-Embedding Predictive Learning of Latent Market States in U.S. Equities
340. ICML 2026KAST-BAR: Knowledge-Anchored Semantically-Dynamic Topology Brain Autoregressive Modeling for Universal Neural Interpretation
341. ICML 2026KnapSpec: Self-Speculative Decoding via Adaptive Layer Selection as a Knapsack Problem
342. ICML 2026Language Model Augmented Semi-Supervised Statistical Inference
343. ICML 2026Learn to Think: Improving Multimodal Reasoning through Vision-Aware Self-Improvement Training
344. ICML 2026Learning Cardiac Latent Representations in Vectorcardiogram Space
345. ICML 2026Learning Randomized Reductions
346. ICML 2026Learning Sparse Visual Representations via Spatial-Semantic Factorization
347. ICML 2026Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining
348. ICML 2026Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation
349. ICML 2026Learning to Self-Verify Makes Language Models Better Reasoners
350. ICML 2026Leveraging Lineage Barcodes as Natural Augmentations for Contrastive Learning of Cell Fate in scRNA-seq Data

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.