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With the implementation of personal data privacy regulations, the field of machine learning (ML) faces the challenge of the "right to be forgotten".
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Certified Data Removal from Machine Learning Models. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event (Proceedings of Machine Learning Research, Vol. 119) . 3832–3842
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Class Clown: Data Redaction in Machine Unlearning at Enterprise Scale. In Proceedings of the 10th International Conference on Operations Research and Enterprise Systems
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Machine Unlearning via Algorithmic Stability. In Conference on Learning Theory, COLT 2021, 15-19 August 2021, Boulder, Colorado, USA (Proceedings of Machine Learning Research, Vol. 134) . 4126–4142
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Panel: Privacy Challenges and Opportunities in { \{ LLM-Based } \} Chatbot Applications
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Nan Xiang, Xiongtao Zhang, Yajie Dou, Xiangqian Xu, Kewei Yang, and Yuejin Tan. 2021 · 2021
Cited alongside, same era.
Counterfactual reward modification for streaming recommendation with delayed feedback. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval . 41–50
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Chong Chen, Fei Sun, Min Zhang, and Bolin Ding. 2022 · 2022
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Editing models with task arithmetic. In The Eleventh International Conference on Learning Representations
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi. 2022 · 2022
Cited alongside, same era.
Knowledge unlearning for mitigating privacy risks in language models
Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, and Minjoon Seo. 2022 · 2022
Cited alongside, same era.
Model inversion attack by integration of deep generative models: Privacy-sensitive face generation from a face recognition system
Mahdi Khosravy, Kazuaki Nakamura, Yuki Hirose, Naoko Nitta, and Noboru Babaguchi. 2022 · 2022
Cited alongside, same era.
Martin Pawelczyk, Seth Neel, and Himabindu Lakkaraju. 2023 · 2023
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Knowledge unlearning for llms: Tasks, methods, and challenges
Nianwen Si, Hao Zhang, Heyu Chang, Wenlin Zhang, Dan Qu, and Weiqiang Zhang. 2023a · 2023
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Knowledge unlearning for llms: Tasks, methods, and challenges
Nianwen Si, Hao Zhang, Heyu Chang, Wenlin Zhang, Dan Qu, and Weiqiang Zhang. 2023b · 2023
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Fast Yet Effective Machine Unlearning
Ayush K. Tarun, Vikram S. Chundawat, Murari Mandal, and Mohan Kankanhalli. 2023 · 2023
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Kga: A general machine unlearning framework based on knowledge gap alignment
Lingzhi Wang, Tong Chen, Wei Yuan, Xingshan Zeng, Kam-Fai Wong, and Hongzhi Yin. 2023 · 2023
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Heng Xu, Tianqing Zhu, Lefeng Zhang, Wanlei Zhou, and Philip S. Yu. 2023 · 2023
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Yuanshun Yao, Xiaojun Xu, and Yang Liu. 2023 · 2023
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Unlearning bias in language models by partitioning gradients. In Findings of the Association for Computational Linguistics: ACL 2023 . 6032–6048
Charles Yu, Sullam Jeoung, Anish Kasi, Pengfei Yu, and Heng Ji. 2023a · 2023
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Gptfuzzer: Red teaming large language models with auto-generated jailbreak prompts
Jiahao Yu, Xingwei Lin, and Xinyu Xing. 2023b · 2023
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Llm for patient-trial matching: Privacy-aware data augmentation towards better performance and generalizability. In American Medical Informatics Association (AMIA) Annual Symposium
Jiayi Yuan, Ruixiang Tang, Xiaoqian Jiang, and Xia Hu. 2023 · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
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Second-Order Information Matters: Revisiting Machine Unlearning for Large Language Models
Kang Gu, Md Rafi Ur Rashid, Najrin Sultana, and Shagufta Mehnaz. 2024 · 2024
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Towards unbounded machine unlearning
Meghdad Kurmanji, Peter Triantafillou, Jamie Hayes, and Eleni Triantafillou. 2024 · 2024
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Machine Unlearning: Taxonomy, Metrics, Applications, Challenges, and Prospects
Na Li, Chunyi Zhou, Yansong Gao, Hui Chen, Anmin Fu, Zhi Zhang, and Yu Shui. 2024 · 2024
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Towards Safer Large Language Models through Machine Unlearning
Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, and Meng Jiang. 2024 · 2024
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Tofu: A task of fictitious unlearning for llms
Pratyush Maini, Zhili Feng, Avi Schwarzschild, Zachary C Lipton, and J Zico Kolter. 2024 · 2024
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Dissecting Language Models: Machine Unlearning via Selective Pruning
Nicholas Pochinkov and Nandi Schoots. 2024 · 2024
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A survey on large language model (llm) security and privacy: The good, the bad, and the ugly
Yifan Yao, Jinhao Duan, Kaidi Xu, Yuanfang Cai, Zhibo Sun, and Yue Zhang. 2024 · 2024
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Composing Parameter-Efficient Modules with Arithmetic Operation
Jinghan Zhang, Junteng Liu, Junxian He, et al · 2024
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