Towards efficient and effective unlearning of large language models for recommendation

Hangyu WANG, Jianghao LIN, Bo CHEN, Yang YANG, Ruiming TANG, Weinan ZHANG, Yong YU

PDF(406 KB)
PDF(406 KB)
Front. Comput. Sci. ›› 2025, Vol. 19 ›› Issue (3) : 193327. DOI: 10.1007/s11704-024-40044-2
Artificial Intelligence
LETTER

Towards efficient and effective unlearning of large language models for recommendation

Author information +
History +

Graphical abstract

Cite this article

Download citation ▾
Hangyu WANG, Jianghao LIN, Bo CHEN, Yang YANG, Ruiming TANG, Weinan ZHANG, Yong YU. Towards efficient and effective unlearning of large language models for recommendation. Front. Comput. Sci., 2025, 19(3): 193327 https://doi.org/10.1007/s11704-024-40044-2

References

[1]
Raffel C, Shazeer N, Roberts A, Lee K, Narang S, Matena M, Zhou Y, Li W, Liu P J. Exploring the limits of transfer learning with a unified text-to-text transformer. The Journal of Machine Learning Research, 2020, 21( 1): 140
[2]
Bourtoule L, Chandrasekaran V, Choquette-Choo C A, Jia H, Travers A, Zhang B, Lie D, Papernot N. Machine unlearning. In: Proceedings of 2021 IEEE Symposium on Security and Privacy. 2021, 141−159
[3]
Chen C, Sun F, Zhang M, Ding B. Recommendation unlearning. In: Proceedings of the ACM Web Conference 2022. 2022, 2768−2777
[4]
Golatkar A, Achille A, Soatto S. Eternal sunshine of the spotless net: Selective forgetting in deep networks. In: Proceedings of 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020, 9301−9309
[5]
Chundawat V S, Tarun A K, Mandal M, Kankanhalli M. Can bad teaching induce forgetting? Unlearning in deep networks using an incompetent teacher. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence. 2023, 7210−7217
[6]
Chen J A, Yang D Y. Unlearn what you want to forget: Efficient unlearning for LLMs. In: Proceedings of 2023 Conference on Empirical Methods in Natural Language Processing. 2023, 12041−12052

Acknowledgements

The SJTU team was supported by the National Natural Science Foundation of China (Grant No. 62177033). The work was sponsored by the Huawei Innovation Research Program. We thank MindSpore for the partial support of this work, which is a new deep learning computing framework.

Competing interests

The authors declare that they have no competing interests or financial conflicts to disclose.

RIGHTS & PERMISSIONS

2025 Higher Education Press
AI Summary AI Mindmap
PDF(406 KB)

Accesses

Citations

Detail

Sections
Recommended

/