{"total":109,"rows":[{"id":"2112.04215","title":"Self-Supervised Models are Continual Learners","created":"2021-12-08","cited_by_count":149,"area":null},{"id":"2201.13100","title":"Adversarial Masking for Self-Supervised Learning","created":"2022-01-31","cited_by_count":78,"area":null},{"id":"2203.16262","title":"How Does SimSiam Avoid Collapse Without Negative Samples? A Unified Understanding with Self-supervised Contrastive Learning","created":"2022-03-30","cited_by_count":65,"area":null},{"id":"2203.17248","title":"Dual Temperature Helps Contrastive Learning Without Many Negative Samples: Towards Understanding and Simplifying MoCo","created":"2022-03-30","cited_by_count":52,"area":null},{"id":"2212.01026","title":"Spectral Feature Augmentation for Graph Contrastive Learning and Beyond","created":"2022-12-02","cited_by_count":49,"area":null},{"id":"2201.10000","title":"Neural Manifold Clustering and Embedding","created":"2022-01-24","cited_by_count":44,"area":null},{"id":"2310.08584","title":"Is ImageNet worth 1 video? Learning strong image encoders from 1 long unlabelled video","created":"2023-10-12","cited_by_count":40,"area":null},{"id":"2305.13689","title":"Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training","created":"2023-05-23","cited_by_count":39,"area":null},{"id":"2209.07999","title":"Self-Supervised Learning with an Information Maximization Criterion","created":"2022-09-16","cited_by_count":38,"area":null},{"id":"2505.12477","title":"Joint Embedding vs Reconstruction: Provable Benefits of Latent Space Prediction for Self Supervised Learning","created":"2025-05-18","cited_by_count":36,"area":null},{"id":"2303.02387","title":"Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism","created":"2023-03-04","cited_by_count":33,"area":null},{"id":"2307.10504","title":"Identifying Interpretable Subspaces in Image Representations","created":"2023-07-20","cited_by_count":32,"area":null},{"id":"2307.12280","title":"Downstream-agnostic Adversarial Examples","created":"2023-07-23","cited_by_count":32,"area":null},{"id":"2303.03307","title":"Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations","created":"2023-03-06","cited_by_count":31,"area":null},{"id":"2310.18555","title":"Group Robust Classification Without Any Group Information","created":"2023-10-28","cited_by_count":25,"area":null},{"id":"2204.00616","title":"Simplicial Embeddings in Self-Supervised Learning and Downstream Classification","created":"2022-04-01","cited_by_count":24,"area":null},{"id":"2206.08871","title":"How Robust is Unsupervised Representation Learning to Distribution Shift?","created":"2022-06-17","cited_by_count":24,"area":null},{"id":"2209.00314","title":"Self-Supervised Pretraining for 2D Medical Image Segmentation","created":"2022-09-01","cited_by_count":24,"area":null},{"id":"2207.10899","title":"Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness","created":"2022-07-22","cited_by_count":20,"area":null},{"id":"2303.01289","title":"Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning","created":"2023-03-02","cited_by_count":20,"area":null},{"id":"2306.07483","title":"Semi-supervised learning made simple with self-supervised clustering","created":"2023-06-13","cited_by_count":20,"area":null},{"id":"2304.03977","title":"EMP-SSL: Towards Self-Supervised Learning in One Training Epoch","created":"2023-04-08","cited_by_count":19,"area":null},{"id":"2308.02346","title":"Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning","created":"2023-08-04","cited_by_count":18,"area":null},{"id":"2206.05259","title":"Is Self-Supervised Learning More Robust Than Supervised Learning?","created":"2022-06-10","cited_by_count":17,"area":null},{"id":"2210.09879","title":"Unsupervised visualization of image datasets using contrastive learning","created":"2022-10-18","cited_by_count":16,"area":null},{"id":"2212.04858","title":"Implicit variance regularization in non-contrastive SSL","created":"2022-12-09","cited_by_count":16,"area":null},{"id":"2303.09417","title":"All4One: Symbiotic Neighbour Contrastive Learning via Self-Attention and Redundancy Reduction","created":"2023-03-16","cited_by_count":11,"area":null},{"id":"2206.08954","title":"Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning","created":"2022-06-17","cited_by_count":10,"area":null},{"id":"2208.05744","title":"On the Pros and Cons of Momentum Encoder in Self-Supervised Visual Representation Learning","created":"2022-08-11","cited_by_count":10,"area":null},{"id":"2306.03962","title":"PILLAR: How to make semi-private learning more effective","created":"2023-06-06","cited_by_count":10,"area":null},{"id":"2404.17249","title":"Making Better Use of Unlabelled Data in Bayesian Active Learning","created":"2024-04-26","cited_by_count":10,"area":null},{"id":"2511.19484","title":"stable-pretraining-v1: Foundation Model Research Made Simple","created":"2025-11-23","cited_by_count":10,"area":null},{"id":"2602.01456","title":"Rectified LpJEPA: Joint-Embedding Predictive Architectures with Sparse and Maximum-Entropy Representations","created":"2026-02-01","cited_by_count":10,"area":null},{"id":"2305.16789","title":"Modulate Your Spectrum in Self-Supervised Learning","created":"2023-05-26","cited_by_count":9,"area":null},{"id":"2411.00392","title":"Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization","created":"2024-11-01","cited_by_count":9,"area":null},{"id":"2411.01777","title":"Learning predictable and robust neural representations by straightening image sequences","created":"2024-11-04","cited_by_count":9,"area":null},{"id":"2304.11357","title":"Learning Symbolic Representations Through Joint GEnerative and DIscriminative Training","created":"2023-04-22","cited_by_count":8,"area":null},{"id":"2307.08919","title":"Systematic comparison of semi-supervised and self-supervised learning for medical image classification","created":"2023-07-18","cited_by_count":8,"area":null},{"id":"2406.10743","title":"Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?","created":"2024-06-15","cited_by_count":8,"area":null},{"id":"2501.18452","title":"Clustering Properties of Self-Supervised Learning","created":"2025-01-30","cited_by_count":8,"area":null},{"id":"2211.02284","title":"Unsupervised Visual Representation Learning via Mutual Information Regularized Assignment","created":"2022-11-04","cited_by_count":7,"area":null},{"id":"2211.09861","title":"Self-Supervised Visual Representation Learning via Residual Momentum","created":"2022-11-17","cited_by_count":7,"area":null},{"id":"2403.13808","title":"On Pretraining Data Diversity for Self-Supervised Learning","created":"2024-03-20","cited_by_count":7,"area":null},{"id":"2410.04959","title":"Collapse-Proof Non-Contrastive Self-Supervised Learning","created":"2024-10-07","cited_by_count":7,"area":null},{"id":"2410.23200","title":"HEX: Hierarchical Emergence Exploitation in Self-Supervised Algorithms","created":"2024-10-30","cited_by_count":7,"area":null},{"id":"2206.06490","title":"Learning Task-Independent Game State Representations from Unlabeled Images","created":"2022-06-13","cited_by_count":6,"area":null},{"id":"2210.09866","title":"Towards Efficient and Effective Self-Supervised Learning of Visual Representations","created":"2022-10-18","cited_by_count":6,"area":null},{"id":"2212.13425","title":"GEDI: GEnerative and DIscriminative Training for Self-Supervised Learning","created":"2022-12-27","cited_by_count":6,"area":null},{"id":"2303.03374","title":"To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning","created":"2023-03-06","cited_by_count":6,"area":null},{"id":"2309.11782","title":"DimCL: Dimensional Contrastive Learning For Improving Self-Supervised Learning","created":"2023-09-21","cited_by_count":6,"area":null},{"id":"2505.01109","title":"Self-Supervision Enhances Instance-based Multiple Instance Learning Methods in Digital Pathology: A Benchmark Study","created":"2025-05-02","cited_by_count":6,"area":null},{"id":"2209.00005","title":"Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning","created":"2022-08-31","cited_by_count":5,"area":null},{"id":"2210.05246","title":"Cluster-level pseudo-labelling for source-free cross-domain facial expression recognition","created":"2022-10-11","cited_by_count":5,"area":null},{"id":"2210.15818","title":"FUSSL: Fuzzy Uncertain Self Supervised Learning","created":"2022-10-28","cited_by_count":5,"area":null},{"id":"2203.01881","title":"Measuring Self-Supervised Representation Quality for Downstream Classification using Discriminative Features","created":"2022-03-03","cited_by_count":4,"area":null},{"id":"2302.10260","title":"Unsupervised Learning on a DIET: Datum IndEx as Target Free of Self-Supervision, Reconstruction, Projector Head","created":"2023-02-20","cited_by_count":4,"area":null},{"id":"2403.02998","title":"Towards Calibrated Deep Clustering Network","created":"2024-03-04","cited_by_count":4,"area":null},{"id":"2403.18266","title":"Branch-Tuning: Balancing Stability and Plasticity for Continual Self-Supervised Learning","created":"2024-03-27","cited_by_count":4,"area":null},{"id":"2505.12576","title":"AdaDim: Dimensionality Adaptation for SSL Representational Dynamics","created":"2025-05-18","cited_by_count":4,"area":null},{"id":"2605.03517","title":"Understanding Self-Supervised Learning via Latent Distribution Matching","created":"2026-05-05","cited_by_count":4,"area":null},{"id":"2208.04592","title":"Comparison of semi-supervised learning methods for High Content Screening quality control","created":"2022-08-09","cited_by_count":3,"area":null},{"id":"2308.04603","title":"A Brief Yet In-Depth Survey of Deep Learning-Based Image Watermarking","created":"2023-08-08","cited_by_count":3,"area":null},{"id":"2309.15420","title":"The Triad of Failure Modes and a Possible Way Out","created":"2023-09-27","cited_by_count":3,"area":null},{"id":"2403.00642","title":"Rethinking The Uniformity Metric in Self-Supervised Learning","created":"2024-03-01","cited_by_count":3,"area":null},{"id":"2403.05966","title":"Can Generative Models Improve Self-Supervised Representation Learning?","created":"2024-03-09","cited_by_count":3,"area":null},{"id":"2506.13717","title":"Contrastive Self-Supervised Learning As Neural Manifold Packing","created":"2025-06-16","cited_by_count":3,"area":null},{"id":"2207.01289","title":"Game State Learning via Game Scene Augmentation","created":"2022-07-04","cited_by_count":2,"area":null},{"id":"2209.14667","title":"Domain-aware Self-supervised Pre-training for Label-Efficient Meme Analysis","created":"2022-09-29","cited_by_count":2,"area":null},{"id":"2305.19818","title":"Spectal Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning","created":"2023-05-31","cited_by_count":2,"area":null},{"id":"2310.00357","title":"Structural Adversarial Objectives for Self-Supervised Representation Learning","created":"2023-09-30","cited_by_count":2,"area":null},{"id":"2310.02903","title":"FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning","created":"2023-10-04","cited_by_count":2,"area":null},{"id":"2401.00873","title":"Unifying Self-Supervised Clustering and Energy-Based Models","created":"2023-12-30","cited_by_count":2,"area":null},{"id":"2405.14669","title":"Efficiency for Free: Ideal Data Are Transportable Representations","created":"2024-05-23","cited_by_count":2,"area":null},{"id":"2407.01804","title":"DCoM: Active Learning for All Learners","created":"2024-07-01","cited_by_count":2,"area":null},{"id":"2506.09781","title":"On the Similarities of Embeddings in Contrastive Learning","created":"2025-06-11","cited_by_count":2,"area":null},{"id":"2507.12359","title":"Cluster Contrast for Unsupervised Visual Representation Learning","created":"2025-07-16","cited_by_count":2,"area":null},{"id":"2510.23484","title":"T-REGS: Minimum Spanning Tree Regularization for Self-Supervised Learning","created":"2025-10-27","cited_by_count":2,"area":null},{"id":"2510.25983","title":"Contrastive Predictive Coding Done Right for Mutual Information Estimation","created":"2025-10-29","cited_by_count":2,"area":null},{"id":"2207.12065","title":"Dynamic Channel Selection in Self-Supervised Learning","created":"2022-07-25","cited_by_count":1,"area":null},{"id":"2305.10675","title":"Tuned Contrastive Learning","created":"2023-05-18","cited_by_count":1,"area":null},{"id":"2409.04747","title":"Explicit Mutual Information Maximization for Self-Supervised Learning","created":"2024-09-07","cited_by_count":1,"area":null},{"id":"2409.06618","title":"Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagery","created":"2024-09-10","cited_by_count":1,"area":null},{"id":"2409.08509","title":"Exploiting Supervised Poison Vulnerability to Strengthen Self-Supervised Defense","created":"2024-09-13","cited_by_count":1,"area":null},{"id":"2410.17427","title":"SigCLR: Sigmoid Contrastive Learning of Visual Representations","created":"2024-10-22","cited_by_count":1,"area":null},{"id":"2501.02966","title":"Human Gaze Boosts Object-Centered Representation Learning","created":"2025-01-06","cited_by_count":1,"area":null},{"id":"2502.03405","title":"Deep Clustering via Probabilistic Ratio-Cut Optimization","created":"2025-02-05","cited_by_count":1,"area":null},{"id":"2504.04318","title":"Variational Self-Supervised Learning","created":"2025-04-06","cited_by_count":1,"area":null},{"id":"2507.21455","title":"Boost Self-Supervised Dataset Distillation via Parameterization, Predefined Augmentation, and Approximation","created":"2025-07-29","cited_by_count":1,"area":null},{"id":"2509.24467","title":"Interpretable Self-Supervised Learning via Representer Landmarks and Nystr\\\"om Approximation","created":"2025-09-29","cited_by_count":1,"area":null},{"id":"2605.09963","title":"Learning to Perceive \"Where\": Spatial Pretext Tasks for Robust Self-Supervised Learning","created":"2026-05-11","cited_by_count":1,"area":null},{"id":"2301.01569","title":"Learning Decorrelated Representations Efficiently Using Fast Fourier Transform","created":"2023-01-04","cited_by_count":0,"area":null},{"id":"2301.09164","title":"Unifying Synergies between Self-supervised Learning and Dynamic Computation","created":"2023-01-22","cited_by_count":0,"area":null},{"id":"2301.11790","title":"Leveraging the Third Dimension in Contrastive Learning","created":"2023-01-27","cited_by_count":0,"area":null},{"id":"2407.05528","title":"An accurate detection is not all you need to combat label noise in web-noisy datasets","created":"2024-07-08","cited_by_count":0,"area":null},{"id":"2409.02140","title":"Self-Supervised Learning for Identifying Defects in Sewer Footage","created":"2024-09-02","cited_by_count":0,"area":null},{"id":"2412.02109","title":"Direct Coloring for Self-Supervised Enhanced Feature Decoupling","created":"2024-12-03","cited_by_count":0,"area":null},{"id":"2412.02121","title":"Rethinking Self-Supervised Learning Within the Framework of Partial Information Decomposition","created":"2024-12-03","cited_by_count":0,"area":null},{"id":"2412.02871","title":"MAGMA: Manifold Regularization for MAEs","created":"2024-12-03","cited_by_count":0,"area":null},{"id":"2412.02896","title":"GUESS: Generative Uncertainty Ensemble for Self Supervision","created":"2024-12-03","cited_by_count":0,"area":null},{"id":"2503.01827","title":"Open-source framework for detecting bias and overfitting for large pathology images","created":"2025-03-03","cited_by_count":0,"area":null}],"next_cursor":"100"}