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 10 of 10

451. NeurIPS 2024Self-supervised Transformation Learning for Equivariant Representations
452. NeurIPS 2024Semi-supervised Multi-label Learning with Balanced Binary Angular Margin Loss
453. NeurIPS 2024SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Models
454. NeurIPS 2024SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models
455. NeurIPS 2024SLIM: Style-Linguistics Mismatch Model for Generalized Audio Deepfake Detection
456. NeurIPS 2024SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams
457. NeurIPS 2024Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks
458. NeurIPS 2024Supervised Kernel Thinning
459. NeurIPS 2024TAIA: Large Language Models are Out-of-Distribution Data Learners
460. NeurIPS 2024The Benefits of Balance: From Information Projections to Variance Reduction
461. NeurIPS 2024Theoretical Analysis of Weak-to-Strong Generalization
462. NeurIPS 2024Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution
463. NeurIPS 2024Towards a theory of how the structure of language is acquired by deep neural networks
464. NeurIPS 2024Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking
465. NeurIPS 2024Uncovering the Redundancy in Graph Self-supervised Learning Models
466. NeurIPS 2024Understanding the Gains from Repeated Self-Distillation
467. NeurIPS 2024Understanding the Role of Equivariance in Self-supervised Learning
468. NeurIPS 2024Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs
469. NeurIPS 2024Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis
470. NeurIPS 2024Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning
471. NeurIPS 2024Where does In-context Learning Happen in Large Language Models?
472. NeurIPS 2024You Don’t Need Domain-Specific Data Augmentations When Scaling Self-Supervised Learning

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.