Fetching the paper…
Reading the bibliography…
While the capabilities of generative foundational models have advanced rapidly in recent years, methods to prevent harmful and unsafe behaviors remain underdeveloped.
Matrix analysis
Horn, R. A. and Johnson, C. R · 2012
Earlier work this paper cites.
Forget-me-not: Learning to forget in text-to-image diffusion models
Zhang, G., Wang, K., Xu, X., Wang, Z., and Shi, H · 2012
Earlier work this paper cites.
Eternal sunshine of the spotless net: Selective forgetting in deep networks
Golatkar, A., Achille, A., and Soatto, S · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
Earlier work this paper cites.
Fastai: a layered api for deep learning
Howard, J. and Gugger, S · 2020
Earlier work this paper cites.
Machine unlearning
Bourtoule, L., Chandrasekaran, V., Choquette-Choo, C. A., Jia, H., Travers, A., Zhang, B., Lie, D., and Papernot, N · 2021
Earlier work this paper cites.
Approximate data deletion from machine learning models
Izzo, Z., Smart, M. A., Chaudhuri, K., and Zou, J · 2021
Earlier work this paper cites.
Descent-to-delete: Gradient-based methods for machine unlearning
Neel, S., Roth, A., and Sharifi-Malvajerdi, S · 2021
Earlier work this paper cites.
Remember what you want to forget: Algorithms for machine unlearning
Sekhari, A., Acharya, J., Kamath, G., and Suresh, A. T · 2021
Earlier work this paper cites.
Machine unlearning of features and labels
Warnecke, A., Pirch, L., Wressnegger, C., and Rieck, K · 2021
Earlier work this paper cites.
High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
Cited alongside, same era.
Unrolling SGD: Understanding Factors Influencing Machine Unlearning
Thudi, A., Deza, G., Chandrasekaran, V., and Papernot, N · 2022
Cited alongside, same era.
Gradient surgery for one-shot unlearning on generative model
Bae, S., Kim, S., Jung, H., and Lim, W · 2023
Cited alongside, same era.
Boundary Unlearning: Rapid Forgetting of Deep Networks via Shifting the Decision Boundary
Chen, M., Gao, W., Liu, G., Peng, K., and Wang, C · 2023
Cited alongside, same era.
Boundary Unlearning: Rapid Forgetting of Deep Networks via Shifting the Decision Boundary
Chen, M., Gao, W., Liu, G., Peng, K., and Wang, C · 2023
Cited alongside, same era.
Towards unbounded machine unlearning
Kurmanji, M., Triantafillou, P., Hayes, J., and Triantafillou, E · 2023
Later among the works it cites.
Safe latent diffusion: Mitigating inappropriate degeneration in diffusion models
Schramowski, P., Brack, M., Deiseroth, B., and Kersting, K · 2023
Later among the works it cites.
Generative adversarial networks unlearning, 2023
Sun, H., Zhu, T., Chang, W., and Zhou, W · 2023
Later among the works it cites.
Deep regression unlearning
Tarun, A. K., Chundawat, V. S., Mandal, M., and Kankanhalli, M · 2023
Later among the works it cites.
Salun: Empowering machine unlearning via gradient-based weight saliency in both image classification and generation
Fan, C., Liu, J., Zhang, Y., Wong, E., Wei, D., and Liu, S · 2024
Later among the works it cites.
Deep unlearning: Fast and efficient gradient-free class forgetting
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Forget unlearning: towards true data-deletion in machine learning
Chourasia, R. and Shah, N · 2023
Cited alongside, same era.
Zero-shot machine unlearning
Chundawat, V. S., Tarun, A. K., Mandal, M., and Kankanhalli, M · 2023
Cited alongside, same era.
Fan, C., Liu, J., Zhang, Y., Wong, E., Wei, D., and Liu, S · 2023
Cited alongside, same era.
Erasing concepts from diffusion models
Gandikota, R., Materzynska, J., Fiotto-Kaufman, J., and Bau, D · 2023
Cited alongside, same era.
Model sparsity can simplify machine unlearning
Jia, J., Liu, J., Ram, P., Yao, Y., Liu, G., Liu, Y., Sharma, P., and Liu, S · 2023
Cited alongside, same era.
Fast model debias with machine unlearning
Chen, R., Yang, J., Xiong, H., Bai, J., Hu, T., Hao, J., FENG, Y., Zhou, J. T., Wu, J., and Liu, Z
Cited in the paper.
Kodge, S., Saha, G., and Roy, K · 2024
Later among the works it cites.
Data Redaction from Conditional Generative Models
Kong, Z. and Chaudhuri, K · 2024
Later among the works it cites.
Machine unlearning for image-to-image generative models
Li, G., Hsu, H., Chen, C.-F., and Marculescu, R · 2024
Later among the works it cites.
Feature unlearning for pre-trained gans and vaes
Moon, S., Cho, S., and Kim, D · 2024
Later among the works it cites.
Sun, C., Wang, R., Zhang, Y., Jia, J., Liu, J., Liu, G., Liu, S., and Yan, Y · 2025
Closest in time.