{"total":77,"rows":[{"id":"2206.09426","title":"ADBench: Anomaly Detection Benchmark","created":"2022-06-19","cited_by_count":232,"area":null},{"id":"2301.05712","title":"A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends","created":"2023-01-13","cited_by_count":207,"area":null},{"id":"2111.13998","title":"Targeted Supervised Contrastive Learning for Long-Tailed Recognition","created":"2021-11-27","cited_by_count":132,"area":null},{"id":"2402.12336","title":"Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models","created":"2024-02-19","cited_by_count":120,"area":"mllm"},{"id":"2308.07026","title":"AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning","created":"2023-08-14","cited_by_count":103,"area":null},{"id":"2210.15318","title":"Efficient and Effective Augmentation Strategy for Adversarial Training","created":"2022-10-27","cited_by_count":43,"area":null},{"id":"2202.05998","title":"What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks?","created":"2022-02-12","cited_by_count":40,"area":null},{"id":"2403.14774","title":"Few-Shot Adversarial Prompt Learning on Vision-Language Models","created":"2024-03-21","cited_by_count":39,"area":"mllm"},{"id":"2202.11202","title":"Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning","created":"2022-02-22","cited_by_count":34,"area":"safety"},{"id":"2210.06284","title":"Visual Prompting for Adversarial Robustness","created":"2022-10-12","cited_by_count":34,"area":null},{"id":"2210.07346","title":"An Embarrassingly Simple Backdoor Attack on Self-supervised Learning","created":"2022-10-13","cited_by_count":31,"area":null},{"id":"2505.15406","title":"Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models","created":"2025-05-21","cited_by_count":21,"area":"safety"},{"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":"2306.01505","title":"Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations","created":"2023-06-02","cited_by_count":19,"area":null},{"id":"2301.12554","title":"Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing","created":"2023-01-29","cited_by_count":18,"area":null},{"id":"2203.14145","title":"Reverse Engineering of Imperceptible Adversarial Image Perturbations","created":"2022-03-26","cited_by_count":17,"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":"2305.09241","title":"Unlearnable Examples Give a False Sense of Security: Piercing through Unexploitable Data with Learnable Examples","created":"2023-05-16","cited_by_count":17,"area":null},{"id":"2210.03372","title":"Pre-trained Adversarial Perturbations","created":"2022-10-07","cited_by_count":16,"area":null},{"id":"2210.13604","title":"The Robustness Limits of SoTA Vision Models to Natural Variation","created":"2022-10-24","cited_by_count":15,"area":null},{"id":"2409.07353","title":"Securing Vision-Language Models with a Robust Encoder Against Jailbreak and Adversarial Attacks","created":"2024-09-11","cited_by_count":15,"area":"mllm"},{"id":"2302.03857","title":"Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection","created":"2023-02-08","cited_by_count":14,"area":null},{"id":"2207.08374","title":"Adversarial Contrastive Learning via Asymmetric InfoNCE","created":"2022-07-18","cited_by_count":13,"area":null},{"id":"2210.00430","title":"Understanding Adversarial Robustness Against On-manifold Adversarial Examples","created":"2022-10-02","cited_by_count":12,"area":null},{"id":"2312.04960","title":"MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness","created":"2023-12-08","cited_by_count":12,"area":"mllm"},{"id":"2407.14971","title":"Sim-CLIP: Unsupervised Siamese Adversarial Fine-Tuning for Robust and Semantically-Rich Vision-Language Models","created":"2024-07-20","cited_by_count":12,"area":"mllm"},{"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":"2202.07201","title":"Holistic Adversarial Robustness of Deep Learning Models","created":"2022-02-15","cited_by_count":11,"area":null},{"id":"2310.08782","title":"Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning","created":"2023-10-13","cited_by_count":11,"area":null},{"id":"2311.18244","title":"Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks","created":"2023-11-30","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":"2308.05681","title":"Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient","created":"2023-08-10","cited_by_count":10,"area":null},{"id":"2210.04782","title":"Robustification of Multilingual Language Models to Real-world Noise in Crosslingual Zero-shot Settings with Robust Contrastive Pretraining","created":"2022-10-10","cited_by_count":9,"area":null},{"id":"2310.01818","title":"AutoLoRa: A Parameter-Free Automated Robust Fine-Tuning Framework","created":"2023-10-03","cited_by_count":9,"area":null},{"id":"2312.09057","title":"On the Difficulty of Defending Contrastive Learning against Backdoor Attacks","created":"2023-12-14","cited_by_count":9,"area":null},{"id":"2210.09643","title":"Improving Adversarial Robustness by Contrastive Guided Diffusion Process","created":"2022-10-18","cited_by_count":8,"area":"diffusion"},{"id":"2304.08479","title":"Towards Robust Prompts on Vision-Language Models","created":"2023-04-17","cited_by_count":7,"area":"mllm"},{"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":"2205.00633","title":"Robust Fine-tuning via Perturbation and Interpolation from In-batch Instances","created":"2022-05-02","cited_by_count":6,"area":null},{"id":"2208.03835","title":"On Transfer of Adversarial Robustness from Pretraining to Downstream Tasks","created":"2022-08-07","cited_by_count":6,"area":null},{"id":"2210.15068","title":"Improving Adversarial Robustness with Self-Paced Hard-Class Pair Reweighting","created":"2022-10-26","cited_by_count":6,"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":"2407.12588","title":"Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks","created":"2024-07-17","cited_by_count":5,"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":"2306.15457","title":"Robust Proxy: Improving Adversarial Robustness by Robust Proxy Learning","created":"2023-06-27","cited_by_count":3,"area":null},{"id":"2210.02989","title":"SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data","created":"2022-10-06","cited_by_count":2,"area":null},{"id":"2210.04076","title":"Robustness of Unsupervised Representation Learning without Labels","created":"2022-10-08","cited_by_count":2,"area":null},{"id":"2210.10482","title":"Effective Targeted Attacks for Adversarial Self-Supervised Learning","created":"2022-10-19","cited_by_count":2,"area":null},{"id":"2211.11711","title":"CLAWSAT: Towards Both Robust and Accurate Code Models","created":"2022-11-21","cited_by_count":2,"area":null},{"id":"2302.12351","title":"On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space","created":"2023-02-23","cited_by_count":2,"area":null},{"id":"2308.03272","title":"Feature-Suppressed Contrast for Self-Supervised Food Pre-training","created":"2023-08-07","cited_by_count":2,"area":null},{"id":"2311.15165","title":"Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off","created":"2023-11-26","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":"2207.05127","title":"RUSH: Robust Contrastive Learning via Randomized Smoothing","created":"2022-07-11","cited_by_count":1,"area":null},{"id":"2209.06971","title":"PointACL:Adversarial Contrastive Learning for Robust Point Clouds Representation under Adversarial Attack","created":"2022-09-14","cited_by_count":1,"area":null},{"id":"2303.07474","title":"Can Adversarial Examples Be Parsed to Reveal Victim Model Information?","created":"2023-03-13","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":"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":"2409.19594","title":"MASKDROID: Robust Android Malware Detection with Masked Graph Representations","created":"2024-09-29","cited_by_count":1,"area":null},{"id":"2602.02542","title":"Auto-Augmentation Contrastive Learning for Wearable-based Human Activity Recognition","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2605.26693","title":"Model Merging on Loss Landscape: A Geometry Perspective","created":"2026-05-26","cited_by_count":1,"area":null},{"id":"2210.03261","title":"Adversarial Lagrangian Integrated Contrastive Embedding for Limited Size Datasets","created":"2022-10-06","cited_by_count":0,"area":null},{"id":"2302.02502","title":"Rethinking Robust Contrastive Learning from the Adversarial Perspective","created":"2023-02-05","cited_by_count":0,"area":null},{"id":"2310.03358","title":"Enhancing Robust Representation in Adversarial Training: Alignment and Exclusion Criteria","created":"2023-10-05","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":"2403.19150","title":"Towards Understanding Dual BN In Hybrid Adversarial Training","created":"2024-03-28","cited_by_count":0,"area":null},{"id":"2404.12635","title":"AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation","created":"2024-04-19","cited_by_count":0,"area":null},{"id":"2406.05796","title":"ProFeAT: Projected Feature Adversarial Training for Self-Supervised Learning of Robust Representations","created":"2024-06-09","cited_by_count":0,"area":null},{"id":"2503.10629","title":"Hierarchical Self-Supervised Adversarial Training for Robust Vision Models in Histopathology","created":"2025-03-13","cited_by_count":0,"area":null},{"id":"2504.10850","title":"How to Enhance Downstream Adversarial Robustness (almost) without Touching the Pre-Trained Foundation Model?","created":"2025-04-15","cited_by_count":0,"area":null},{"id":"2505.23933","title":"BIRD: Behavior Induction via Representation-structure Distillation","created":"2025-05-29","cited_by_count":0,"area":null},{"id":"2604.14973","title":"Robustness of Vision Foundation Models to Common Perturbations","created":"2026-04-16","cited_by_count":0,"area":null},{"id":"2604.22540","title":"On the Properties of Feature Attribution for Supervised Contrastive Learning","created":"2026-04-24","cited_by_count":0,"area":null},{"id":"2607.21243","title":"Detectors Learn the Wrong Thing: Shortcut-Resistant Adversarial Training Against Physically Realizable Attacks","created":"2026-07-23","cited_by_count":0,"area":null},{"id":"2610.13281","title":"QCLR: A Plug-in Robustification Module via Quantization for Contrastive Learning in Self-Supervised Skeleton-Based Human Action Recognition","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}