深度学习 · self supervised learning论文趋势 2023–2026
ICML/NeurIPS 深度学习方向：self_supervised_learning
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,958 篇被归入该主题的论文。
主要结论
- 深度学习 · self supervised learning论文从 2023 年的 455 篇增长到 2026 年的 534 篇，三年间扩大到约 1.2 倍。
- ICLR 是发深度学习 · self supervised learning论文最多的会议，2023–2026 年共 693 篇，占四个会议总量的 35%。
- 交叉方向里涨得最快的是通用机器学习 · unsupervised and semisupervised learning：同时属于两个主题的论文从 2023 年的 23 篇增至 2026 年的 86 篇。
- 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 4；同组增长最快的扩散模型是 4.1 倍，深度学习 · self supervised learning是 1.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 160 | 108 | 41 | 146 | 455 |
| 2024 | 110 | 195 | 62 | 105 | 472 |
| 2025 | 147 | 195 | 72 | 83 | 497 |
| 2026 | 110 | 195 | 135 | 94 | 534 |
代表论文
按年份和会议均匀挑选，方便快速看到每一届的样貌
- 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
全部深度学习 · self supervised learning论文
共 693 篇，第 14 / 14 页
- ICLR 2023Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play
- ICLR 2023Rethinking Self-Supervised Visual Representation Learning in Pre-training for 3D Human Pose and Shape Estimation
- ICLR 2023Robust Active Distillation
- ICLR 2023RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
- ICLR 2023Sampling-free Inference for Ab-Initio Potential Energy Surface Networks
- ICLR 2023Scaling Forward Gradient With Local Losses
- ICLR 2023Self-Consistency Improves Chain of Thought Reasoning in Language Models
- ICLR 2023Self-Distillation for Further Pre-training of Transformers
- ICLR 2023Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors
- ICLR 2023Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability
- ICLR 2023Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance
- ICLR 2023Self-Supervised Geometric Correspondence for Category-Level 6D Object Pose Estimation in the Wild
- ICLR 2023Self-supervised learning with rotation-invariant kernels
- ICLR 2023Self-Supervised Set Representation Learning for Unsupervised Meta-Learning
- ICLR 2023Self-supervision through Random Segments with Autoregressive Coding (RandSAC)
- ICLR 2023Semi-supervised Community Detection via Structural Similarity Metrics
- ICLR 2023Semi-supervised learning with a principled likelihood from a generative model of data curation
- ICLR 2023SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations
- ICLR 2023SimPer: Simple Self-Supervised Learning of Periodic Targets
- ICLR 2023Simplicial Embeddings in Self-Supervised Learning and Downstream Classification
- ICLR 2023SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning
- ICLR 2023Spectral Augmentation for Self-Supervised Learning on Graphs
- ICLR 2023STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables
- ICLR 2023Temperature Schedules for self-supervised contrastive methods on long-tail data
- ICLR 2023The hidden uniform cluster prior in self-supervised learning
- ICLR 2023The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning
- ICLR 2023Time to augment self-supervised visual representation learning
- ICLR 2023Towards Better Selective Classification
- ICLR 2023Towards the Generalization of Contrastive Self-Supervised Learning
- ICLR 2023Transformer-based model for symbolic regression via joint supervised learning
- ICLR 2023Transformers Learn Shortcuts to Automata
- ICLR 2023Truthful Self-Play
- ICLR 2023Unbiased Supervised Contrastive Learning
- ICLR 2023Understanding The Robustness of Self-supervised Learning Through Topic Modeling
- ICLR 2023Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning
- ICLR 2023Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning
- ICLR 2023Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations
- ICLR 2023ViewCo: Discovering Text-Supervised Segmentation Masks via Multi-View Semantic Consistency
- ICLR 2023VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training
- ICLR 2023Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning
- ICLR 2023Weighted Ensemble Self-Supervised Learning
- ICLR 2023What Do Self-Supervised Vision Transformers Learn?
- ICLR 2023What shapes the loss landscape of self supervised learning?
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可以直接复制这句话问 AI
用 paperlist 查深度学习 · self supervised learning在 ICLR 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "dl-self-supervised-learning"}
常见问题
- 2023–2026 年四大会议一共有多少篇深度学习 · self supervised learning论文？
- 共 1,958 篇，按年份分别是 2023 年 455 篇、2024 年 472 篇、2025 年 497 篇、2026 年 534 篇。
- NeurIPS 2026 有多少篇深度学习 · self supervised learning论文？
- NeurIPS 2026 有 110 篇深度学习 · self supervised learning论文，上一届是 147 篇。
- ICLR 2026 有多少篇深度学习 · self supervised learning论文？
- ICLR 2026 有 195 篇深度学习 · self supervised learning论文，上一届是 195 篇。
- ICML 2026 有多少篇深度学习 · self supervised learning论文？
- ICML 2026 有 135 篇深度学习 · self supervised learning论文，上一届是 72 篇。
- CVPR 2026 有多少篇深度学习 · self supervised learning论文？
- CVPR 2026 有 94 篇深度学习 · self supervised learning论文，上一届是 83 篇。
- 哪个会议的深度学习 · self supervised learning论文最多？
- ICLR，2023–2026 年共 693 篇。