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← Learning Types
Machine Learning
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Adversarial Learning
4,854 papers
Papers per year
2006: 3
2007: 1
2009: 4
2010: 6
2011: 3
2012: 5
2013: 10
2014: 6
2015: 8
2016: 18
2017: 87
2018: 261
2019: 551
2020: 588
2021: 703
2022: 633
2023: 672
2024: 579
2025: 561
2026: 155
Papers
Improving Robustness Against Stealthy Weight Bit-Flip Attacks by Output Code Matching
CVPR 2022
On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles
CVPR 2022
Leveraging Adversarial Examples To Quantify Membership Information Leakage
CVPR 2022
DetectorDetective: Investigating the Effects of Adversarial Examples on Object Detectors
CVPR 2022
Stereoscopic Universal Perturbations Across Different Architectures and Datasets
CVPR 2022
FIBA: Frequency-Injection Based Backdoor Attack in Medical Image Analysis
CVPR 2022
Protecting Celebrities From DeepFake With Identity Consistency Transformer
CVPR 2022
Give Me Your Attention: Dot-Product Attention Considered Harmful for Adversarial Patch Robustness
CVPR 2022
Fairness-Aware Adversarial Perturbation Towards Bias Mitigation for Deployed Deep Models
CVPR 2022
NashAE: Disentangling Representations through Adversarial Covariance Minimization
ECCV 2022
Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient Ensembling
EMNLP 2022
Balanced Adversarial Training: Balancing Tradeoffs between Fickleness and Obstinacy in NLP Models
EMNLP 2022
Deconfounding Legal Judgment Prediction for European Court of Human Rights Cases Towards Better Alignment with Experts
EMNLP 2022
Extracted BERT Model Leaks More Information than You Think!
EMNLP 2022
Red Teaming Language Models with Language Models
EMNLP 2022
Rethinking Style Transformer with Energy-based Interpretation: Adversarial Unsupervised Style Transfer using a Pretrained Model
EMNLP 2022
TABS: Efficient Textual Adversarial Attack for Pre-trained NL Code Model Using Semantic Beam Search
EMNLP 2022
Adversarial Concept Erasure in Kernel Space
EMNLP 2022
Learning Robust Representations for Continual Relation Extraction via Adversarial Class Augmentation
EMNLP 2022
ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation
EMNLP 2022
Precisely the Point: Adversarial Augmentations for Faithful and Informative Text Generation
EMNLP 2022
Debiasing Masks: A New Framework for Shortcut Mitigation in NLU
EMNLP 2022
Text Style Transferring via Adversarial Masking and Styled Filling
EMNLP 2022
Character-level White-Box Adversarial Attacks against Transformers via Attachable Subwords Substitution
EMNLP 2022
Efficient Adversarial Training with Robust Early-Bird Tickets
EMNLP 2022
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