{"total":91,"rows":[{"id":"2202.03104","title":"SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation","created":"2022-02-07","cited_by_count":171,"area":null},{"id":"2105.00470","title":"On Feature Decorrelation in Self-Supervised Learning","created":"2021-05-02","cited_by_count":160,"area":null},{"id":"2108.00401","title":"Advances in adversarial attacks and defenses in computer vision: A survey","created":"2021-08-01","cited_by_count":127,"area":null},{"id":"2106.11230","title":"Can contrastive learning avoid shortcut solutions?","created":"2021-06-21","cited_by_count":114,"area":null},{"id":"2203.07004","title":"Rethinking Minimal Sufficient Representation in Contrastive Learning","created":"2022-03-14","cited_by_count":69,"area":null},{"id":"2109.02973","title":"Unpaired Deep Image Deraining Using Dual Contrastive Learning","created":"2021-09-07","cited_by_count":60,"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":"2111.09613","title":"Improving Transferability of Representations via Augmentation-Aware Self-Supervision","created":"2021-11-18","cited_by_count":49,"area":null},{"id":"2110.12764","title":"Contrastive Learning for Neural Topic Model","created":"2021-10-25","cited_by_count":48,"area":null},{"id":"2107.02575","title":"Contrastive Multimodal Fusion with TupleInfoNCE","created":"2021-07-06","cited_by_count":43,"area":null},{"id":"2110.14189","title":"Robust Contrastive Learning Using Negative Samples with Diminished Semantics","created":"2021-10-27","cited_by_count":43,"area":null},{"id":"2202.06491","title":"Adversarial Graph Contrastive Learning with Information Regularization","created":"2022-02-14","cited_by_count":38,"area":null},{"id":"2202.13093","title":"Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding","created":"2022-02-26","cited_by_count":25,"area":null},{"id":"2408.09929","title":"Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise","created":"2024-08-19","cited_by_count":25,"area":null},{"id":"2202.07470","title":"Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning","created":"2022-02-14","cited_by_count":21,"area":null},{"id":"2105.10843","title":"Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation","created":"2021-05-23","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":"2309.13439","title":"Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning","created":"2023-09-23","cited_by_count":18,"area":null},{"id":"2301.13487","title":"Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World Attacks","created":"2023-01-31","cited_by_count":17,"area":null},{"id":"2102.13085","title":"Towards Robust Graph Contrastive Learning","created":"2021-02-25","cited_by_count":16,"area":null},{"id":"2103.01895","title":"Adversarial Examples can be Effective Data Augmentation for Unsupervised Machine Learning","created":"2021-03-02","cited_by_count":16,"area":null},{"id":"2402.17238","title":"Does Negative Sampling Matter? A Review with Insights into its Theory and Applications","created":"2024-02-27","cited_by_count":15,"area":null},{"id":"2302.03857","title":"Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection","created":"2023-02-08","cited_by_count":14,"area":null},{"id":"2203.13455","title":"A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training","created":"2022-03-25","cited_by_count":13,"area":null},{"id":"2204.02553","title":"RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection","created":"2022-04-06","cited_by_count":13,"area":null},{"id":"2202.06464","title":"Synthetic Data Can Also Teach: Synthesizing Effective Data for Unsupervised Visual Representation Learning","created":"2022-02-14","cited_by_count":12,"area":null},{"id":"2108.13797","title":"Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings","created":"2021-08-30","cited_by_count":11,"area":null},{"id":"2112.04468","title":"Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework","created":"2021-12-08","cited_by_count":11,"area":null},{"id":"2203.05335","title":"Non-generative Generalized Zero-shot Learning via Task-correlated Disentanglement and Controllable Samples Synthesis","created":"2022-03-10","cited_by_count":11,"area":null},{"id":"2410.20380","title":"FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion","created":"2024-10-27","cited_by_count":11,"area":null},{"id":"2305.00374","title":"Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization","created":"2023-04-30","cited_by_count":10,"area":null},{"id":"2305.15924","title":"Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation","created":"2023-05-25","cited_by_count":10,"area":null},{"id":"2203.14370","title":"CaCo: Both Positive and Negative Samples are Directly Learnable via Cooperative-adversarial Contrastive Learning","created":"2022-03-27","cited_by_count":9,"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":"2106.03259","title":"Understand and Improve Contrastive Learning Methods for Visual Representation: A Review","created":"2021-06-06","cited_by_count":7,"area":null},{"id":"2110.07439","title":"Inverse Problems Leveraging Pre-trained Contrastive Representations","created":"2021-10-14","cited_by_count":7,"area":null},{"id":"2407.01312","title":"ToCoAD: Two-Stage Contrastive Learning for Industrial Anomaly Detection","created":"2024-07-01","cited_by_count":7,"area":null},{"id":"2408.01978","title":"AdvQDet: Detecting Query-Based Adversarial Attacks with Adversarial Contrastive Prompt Tuning","created":"2024-08-04","cited_by_count":7,"area":null},{"id":"2204.09838","title":"Fast AdvProp","created":"2022-04-21","cited_by_count":6,"area":null},{"id":"2211.00824","title":"Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach","created":"2022-11-02","cited_by_count":6,"area":null},{"id":"2302.10633","title":"Generalization Bounds for Adversarial Contrastive Learning","created":"2023-02-21","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":"2312.07392","title":"ReRoGCRL: Representation-based Robustness in Goal-Conditioned Reinforcement Learning","created":"2023-12-12","cited_by_count":6,"area":null},{"id":"2208.06956","title":"ARIEL: Adversarial Graph Contrastive Learning","created":"2022-08-15","cited_by_count":5,"area":null},{"id":"2208.11278","title":"Federated Self-Supervised Contrastive Learning and Masked Autoencoder for Dermatological Disease Diagnosis","created":"2022-08-24","cited_by_count":5,"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":"2210.12874","title":"Global Contrastive Batch Sampling via Optimization on Sample Permutations","created":"2022-10-23","cited_by_count":5,"area":null},{"id":"2302.05783","title":"ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction","created":"2023-02-11","cited_by_count":5,"area":null},{"id":"2302.14302","title":"Improving Model Generalization by On-manifold Adversarial Augmentation in the Frequency Domain","created":"2023-02-28","cited_by_count":5,"area":null},{"id":"2402.12187","title":"Adversarial Feature Alignment: Balancing Robustness and Accuracy in Deep Learning via Adversarial Training","created":"2024-02-19","cited_by_count":5,"area":null},{"id":"2406.05857","title":"Self-supervised Adversarial Training of Monocular Depth Estimation against Physical-World Attacks","created":"2024-06-09","cited_by_count":5,"area":null},{"id":"2407.12588","title":"Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks","created":"2024-07-17","cited_by_count":5,"area":null},{"id":"2411.02149","title":"Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training","created":"2024-11-04","cited_by_count":5,"area":null},{"id":"2111.03169","title":"Hard Negative Sampling via Regularized Optimal Transport for Contrastive Representation Learning","created":"2021-11-04","cited_by_count":4,"area":null},{"id":"2111.10154","title":"Small Changes Make Big Differences: Improving Multi-turn Response Selection in Dialogue Systems via Fine-Grained Contrastive Learning","created":"2021-11-19","cited_by_count":4,"area":null},{"id":"2111.13301","title":"Simple Contrastive Representation Adversarial Learning for NLP Tasks","created":"2021-11-26","cited_by_count":4,"area":null},{"id":"2202.06996","title":"Unlabeled Data Help: Minimax Analysis and Adversarial Robustness","created":"2022-02-14","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":"2210.11498","title":"Balanced Adversarial Training: Balancing Tradeoffs between Fickleness and Obstinacy in NLP Models","created":"2022-10-20","cited_by_count":3,"area":null},{"id":"2210.13463","title":"Adversarial Pretraining of Self-Supervised Deep Networks: Past, Present and Future","created":"2022-10-23","cited_by_count":3,"area":null},{"id":"2305.10563","title":"HaSa: Hardness and Structure-Aware Contrastive Knowledge Graph Embedding","created":"2023-05-17","cited_by_count":3,"area":null},{"id":"2309.16633","title":"SupReMix: Supervised Contrastive Learning for Medical Imaging Regression with Mixup","created":"2023-09-28","cited_by_count":3,"area":null},{"id":"2210.04076","title":"Robustness of Unsupervised Representation Learning without Labels","created":"2022-10-08","cited_by_count":2,"area":null},{"id":"2212.00953","title":"Few-Shot Nested Named Entity Recognition","created":"2022-12-02","cited_by_count":2,"area":null},{"id":"2310.03707","title":"OMG-ATTACK: Self-Supervised On-Manifold Generation of Transferable Evasion Attacks","created":"2023-10-05","cited_by_count":2,"area":null},{"id":"2509.23373","title":"Graph Your Own Prompt","created":"2025-09-27","cited_by_count":2,"area":null},{"id":"2510.27249","title":"C-LEAD: Contrastive Learning for Enhanced Adversarial Defense","created":"2025-10-31","cited_by_count":2,"area":null},{"id":"2604.07994","title":"SAT: Selective Aggregation Transformer for Image Super-Resolution","created":"2026-04-09","cited_by_count":2,"area":null},{"id":"2103.13612","title":"THAT: Two Head Adversarial Training for Improving Robustness at Scale","created":"2021-03-25","cited_by_count":1,"area":null},{"id":"2202.12860","title":"ARIA: Adversarially Robust Image Attribution for Content Provenance","created":"2022-02-25","cited_by_count":1,"area":null},{"id":"2207.10862","title":"Contrastive Self-Supervised Learning Leads to Higher Adversarial Susceptibility","created":"2022-07-22","cited_by_count":1,"area":null},{"id":"2305.00623","title":"A Simplified Framework for Contrastive Learning for Node Representations","created":"2023-05-01","cited_by_count":1,"area":null},{"id":"2402.09239","title":"Robust Training of Temporal GNNs using Nearest Neighbours based Hard Negatives","created":"2024-02-14","cited_by_count":1,"area":null},{"id":"2409.12946","title":"Revisiting Semi-supervised Adversarial Robustness via Noise-aware Online Robust Distillation","created":"2024-09-19","cited_by_count":1,"area":null},{"id":"2409.14401","title":"Investigating the Impact of Hard Samples on Accuracy Reveals In-class Data Imbalance","created":"2024-09-22","cited_by_count":1,"area":null},{"id":"2412.16522","title":"Enhancing Contrastive Learning Inspired by the Philosophy of \"The Blind Men and the Elephant\"","created":"2024-12-21","cited_by_count":1,"area":null},{"id":"2503.06361","title":"Adversarial Robustness of Discriminative Self-Supervised Learning in Vision","created":"2025-03-08","cited_by_count":1,"area":null},{"id":"2602.09066","title":"Spectral Disentanglement and Enhancement: A Dual-domain Contrastive Framework for Representation Learning","created":"2026-02-09","cited_by_count":1,"area":null},{"id":"2206.04472","title":"Early Transferability of Adversarial Examples in Deep Neural Networks","created":"2022-06-09","cited_by_count":0,"area":null},{"id":"2211.16253","title":"Advancing Deep Metric Learning Through Multiple Batch Norms And Multi-Targeted Adversarial Examples","created":"2022-11-29","cited_by_count":0,"area":null},{"id":"2305.13678","title":"Enhancing Accuracy and Robustness through Adversarial Training in Class Incremental Continual Learning","created":"2023-05-23","cited_by_count":0,"area":null},{"id":"2311.09671","title":"Generalization Bounds for Robust Contrastive Learning: From Theory to Practice","created":"2023-11-16","cited_by_count":0,"area":null},{"id":"2401.15248","title":"Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective","created":"2024-01-26","cited_by_count":0,"area":null},{"id":"2405.18931","title":"EntProp: High Entropy Propagation for Improving Accuracy and Robustness","created":"2024-05-29","cited_by_count":0,"area":null},{"id":"2407.12782","title":"Contrastive Adversarial Training for Unsupervised Domain Adaptation","created":"2024-07-17","cited_by_count":0,"area":null},{"id":"2410.02512","title":"SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation","created":"2024-10-03","cited_by_count":0,"area":null},{"id":"2507.13727","title":"Adversarial Training Improves Generalization Under Distribution Shifts in Bird Sound Classification","created":"2025-07-18","cited_by_count":0,"area":null},{"id":"2510.01853","title":"Learning Representations Through Contrastive Neural Model Checking","created":"2025-10-02","cited_by_count":0,"area":null},{"id":"2511.20997","title":"FANoise: Singular Value-Adaptive Noise Modulation for Robust Multimodal Representation Learning","created":"2025-11-26","cited_by_count":0,"area":null},{"id":"2603.16338","title":"SpikeCLR: Contrastive Self-Supervised Learning for Few-Shot Event-Based Vision using Spiking Neural Networks","created":"2026-03-17","cited_by_count":0,"area":null},{"id":"2604.01878","title":"ASPECT: Node-Level Adaptive Spectral Fusion for Graph Contrastive Learning","created":"2026-04-02","cited_by_count":0,"area":null}],"next_cursor":null}