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The proliferation of large AI models trained on uncurated, often sensitive web-scraped data has raised significant privacy concerns.
Automated Flower Classification over a Large Number of Classes
M.-E. Nilsback and A. Zisserman · 2008
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ImageNet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Learning multiple layers of features from tiny images
A. Krizhevsky · 2009
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SUN Database: Large-scale Scene Recognition from Abbey to Zoo
J. Xiao, J. Hays, K. A. Ehinger, A. Oliva, and A. Torralba · 2010
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Microsoft COCO: Common Objects in Context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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A data-driven approach to cleaning large face datasets
H.-W. Ng and S. Winkler · 2014
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Towards Making Systems Forget with Machine Unlearning
Y. Cao and J. Yang · 2015
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Model Inversion Attacks That Exploit Confidence Information and Basic Countermeasures
M. Fredrikson, S. Jha, and T. Ristenpart · 2015
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BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
T. Gu, B. Dolan-Gavitt, and S. Garg · 2017
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Membership Inference Attacks Against Machine Learning Models
R. Shokri, M. Stronati, C. Song, and V. Shmatikov · 2017
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Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring
Y. Adi, C. Baum, M. Cisse, B. Pinkas, and J. Keshet · 2018
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Trojaning Attack on Neural Networks
Y. Liu, S. Ma, Y. Aafer, W. Lee, J. Zhai, W. Wang, and X. Zhang · 2018
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Spectral Signatures in Backdoor Attacks
B. Tran, J. Li, and A. Madry · 2018
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Making AI Forget You: Data Deletion in Machine Learning
A. Ginart, M. Guan, G. Valiant, and J. Y. Zou · 2019
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Parameter-Efficient Transfer Learning for NLP
N. Houlsby, A. Giurgiu, S. Jastrzebski, B. Morrone, Q. De Laroussilhe, A. Gesmundo, M. Attariyan, and S. Gelly · 2019
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Do ImageNet Classifiers Generalize to ImageNet?
B. Recht, R. Roelofs, L. Schmidt, and V. Shankar · 2019
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Certified Data Removal from Machine Learning Models
C. Guo, T. Goldstein, A. Hannun, and L. Van Der Maaten · 2020
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Hidden Trigger Backdoor Attacks
A. Saha, A. Subramanya, and H. Pirsiavash · 2020
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Towards Probabilistic Verification of Machine Unlearning
D. M. Sommer, L. Song, S. Wagh, and P. Mittal · 2020
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The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks
Y. Zhang, R. Jia, H. Pei, W. Wang, B. Li, and D. Song · 2020
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Machine Unlearning
L. Bourtoule, V. Chandrasekaran, C. A. Choquette-Choo, H. Jia, A. Travers, B. Zhang, D. Lie, and N. Papernot · 2021
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Extracting Training Data from Large Language Models
N. Carlini et al · 2021
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BadNL: Backdoor Attacks against NLP Models with Semantic-Preserving Improvements
X. Chen, A. Salem, D. Chen, M. Backes, S. Ma, Q. Shen, Z. Wu, and Y. Zhang · 2021
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Amnesiac Machine Learning
L. Graves, V. Nagisetty, and V. Ganesh · 2021
Backdoor Attacks on Self-Supervised Learning
A. Saha, A. Tejankar, S. A. Koohpayegani, and H. Pirsiavash · 2022
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LAION-5B: An open large-scale dataset for training next generation image-text models
C. Schuhmann et al · 2022
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Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks
L. Struppek, D. Hintersdorf, A. De Almeida Correira, A. Adler, and K. Kersting · 2022
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Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets
F. Tramèr, R. Shokri, A. San Joaquin, H. Le, M. Jagielski, S. Hong, and N. Carlini · 2022
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ARCANE: An Efficient Architecture for Exact Machine Unlearning
H. Yan, X. Li, Z. Guo, H. Li, F. Li, and X. Lin · 2022
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California Consumer Privacy Act of 2018
California Legislative Information · 2023
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Cited alongside, same era.
OpenCLIP, 2021
G. Ilharco et al · 2021
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Approximate Data Deletion from Machine Learning Models
Z. Izzo, M. Anne Smart, K. Chaudhuri, and J. Zou · 2021
Cited alongside, same era.
Hidden Backdoors in Human-Centric Language Models
S. Li, H. Liu, T. Dong, B. Z. H. Zhao, M. Xue, H. Zhu, and J. Lu · 2021
Cited alongside, same era.
EncoderMI: Membership Inference against Pre-Trained Encoders in Contrastive Learning
H. Liu, J. Jia, W. Qu, and N. Z. Gong · 2021
Cited alongside, same era.
Learning Transferable Visual Models From Natural Language Supervision
A. Radford et al · 2021
Cited alongside, same era.
Poisoning and Backdooring Contrastive Learning
N. Carlini and A. Terzis · 2022
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How to Backdoor Diffusion Models?
S.-Y. Chou, P.-Y. Chen, and T.-Y. Ho · 2023
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Zero-Shot Machine Unlearning
V. S. Chundawat, A. K. Tarun, M. Mandal, and M. S. Kankanhalli · 2023
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Artist finds private medical record photos in popular AI training data set
B. Edwards · 2023
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Regulation (EU) 2016/679 of the European Parliament
European Parliament and European Council · 2023
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What does GPT-3 “know” about me?
M. Heikkilä · 2023
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Towards Unbounded Machine Unlearning
M. Kurmanji, P. Triantafillou, J. Hayes, and E. Triantafillou · 2023
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Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis
L. Struppek, D. Hintersdorf, and K. Kersting · 2023
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Frequently Occurring Surnames from the 2010 Census
United States Census Bureau · 2023
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data-baby-names
H. Wickham · 2023
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Machine Unlearning by Reversing the Continual Learning
Y. Zhang, Z. Lu, F. Zhang, H. Wang, and S. Li · 2023
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Does CLIP Know My Face?
D. Hintersdorf, L. Struppek, M. Brack, F. Friedrich, P. Schramowski, and K. Kersting · 2024
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