UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Moral foundations of products liability law: Toward first principles

D. G. Owen · 1992

Earlier work this paper cites.

Responsibility and Control: A Theory of Moral Responsibility

J. M. Fischer and M. Ravizza · 1998

Earlier work this paper cites.

Making ai forget you: Data deletion in machine learning

A. Ginart, M. Guan, G. Valiant, and J. Y. Zou · 2019

Earlier work this paper cites.

Language models are few-shot learners

T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, and D. Amodei · 2020

Earlier work this paper cites.

Eternal sunshine of the spotless net: Selective forgetting in deep networks

A. Golatkar, A. Achille, and S. Soatto · 2020

Earlier work this paper cites.

Machine unlearning

L. Bourtoule, V. Chandrasekaran, C. A. Choquette-Choo, H. Jia, A. Travers, B. Zhang, D. Lie, and N. Papernot · 2021

Earlier work this paper cites.

Remember what you want to forget: Algorithms for machine unlearning

A. Sekhari, J. Acharya, G. Kamath, and A. T. Suresh · 2021

Earlier work this paper cites.

Backdoor defense with machine unlearning

Y. Liu, M. Fan, C. Chen, X. Liu, Z. Ma, L. Wang, and J. Ma · 2022

Earlier work this paper cites.

On the necessity of auditable algorithmic definitions for machine unlearning

A. Thudi, H. Jia, I. Shumailov, and N. Papernot · 2022

Earlier work this paper cites.

In differential privacy, there is truth: on vote-histogram leakage in ensemble private learning

J. Wang, R. Schuster, I. Shumailov, D. Lie, and N. Papernot · 2022

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Who’s harry potter? approximate unlearning in llms, 2023

R. Eldan and M. Russinovich · 2023

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Salun: Empowering machine unlearning via gradient-based weight saliency in both image classification and generation

Original

C. Fan, J. Liu, Y. Zhang, D. Wei, E. Wong, and S. Liu · 2023

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LLM censorship: A machine learning challenge or a computer security problem?, 2023

D. Glukhov, I. Shumailov, Y. Gal, N. Papernot, and V. Papyan · 2023

Cited alongside, same era.

Self-destructing models: Increasing the costs of harmful dual uses of foundation models

P. Henderson, E. Mitchell, C. Manning, D. Jurafsky, and C. Finn · 2023

Cited alongside, same era.

Corrective machine unlearning

Original

S. Goel, A. Prabhu, P. Torr, P. Kumaraguru, and A. Sanyal · 2024

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Inexact unlearning needs more careful evaluations to avoid a false sense of privacy, 2024

J. Hayes, I. Shumailov, E. Triantafillou, A. Khalifa, and N. Papernot · 2024

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In-context learning learns label relationships but is not conventional learning

J. Kossen, Y. Gal, and T. Rainforth · 2024

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Towards unbounded machine unlearning

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The wmdp benchmark: Measuring and reducing malicious use with unlearning, 2024

N. Li, A. Pan, A. Gopal, S. Yue, D. Berrios, A. Gatti, J. D. Li, A.-K. Dombrowski, S. Goel, L. Phan, G. Mukobi, N. Helm-Burger, R. Lababidi, L. Justen, A. B. Liu, M. Chen, I. Barrass, O. Zhang, X. Zhu, R. Tamirisa, B. Bharathi, A. Khoja, A. Herbert-Voss, C. B. Breuer, A. Zou, M. Mazeika, Z. Wang, P. Oswal, W. Liu, A. A. Hunt, J. Tienken-Harder, K. Y. Shih, K. Talley, J. Guan, R. Kaplan, I. Steneker, D. Campbell, B. Jokubaitis, A. Levinson, J. Wang, W. Qian, K. K. Karmakar, S. Basart, S. Fitz, M. Levine, P. Kumaraguru, U. Tupakula, V. Varadharajan, Y. Shoshitaishvili, J. Ba, K. M. Esvelt, A. Wang, and D. Hendrycks · 2024