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Locate-then-Edit Knowledge Editing (LEKE) is a key technique for updating large language models (LLMs) without full retraining.
Pearson correlation coefficient
Israel Cohen, Yiteng Huang, Jingdong Chen, Jacob Benesty, Jacob Benesty, Jingdong Chen, Yiteng Huang, and Israel Cohen. 2009 · 2009
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Federated learning: Strategies for improving communication efficiency
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Zero-shot relation extraction via reading comprehension
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Applied federated learning: Improving google keyboard query suggestions
Timothy Yang, Galen Andrew, Hubert Eichner, Haicheng Sun, Wei Li, Nicholas Kong, Daniel Ramage, and Françoise Beaufays. 2018 · 2018
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Gpt-j-6b: A 6 billion parameter autoregressive language model
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Differential privacy for deep and federated learning: A survey
Ahmed El Ouadrhiri and Ahmed Abdelhadi. 2022 · 2022
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Memory-based model editing at scale
Eric Mitchell, Charles Lin, Antoine Bosselut, Christopher D Manning, and Chelsea Finn. 2022 · 2022
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Where to begin? on the impact of pre-training and initialization in federated learning
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Integration of large language models and federated learning
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Rebuilding rome: Resolving model collapse during sequential model editing
Akshat Gupta, Sidharth Baskaran, and Gopala Anumanchipalli. 2024 · 2024
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Can knowledge editing really correct hallucinations?
Baixiang Huang, Canyu Chen, Xiongxiao Xu, Ali Payani, and Kai Shu. 2024 · 2024
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Language-guided transformer for federated multi-label classification
I-Jieh Liu, Ci-Siang Lin, Fu-En Yang, and Yu-Chiang Frank Wang. 2024 · 2024
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Detoxifying large language models via knowledge editing
Mengru Wang, Ningyu Zhang, Ziwen Xu, Zekun Xi, Shumin Deng, Yunzhi Yao, Qishen Zhang, Linyi Yang, Jindong Wang, and Huajun Chen. 2024 · 2024
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Editing large language models: Problems, methods, and opportunities
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Pmet: Precise model editing in a transformer
Xiaopeng Li, Shasha Li, Shezheng Song, Jing Yang, Jun Ma, and Jie Yu. 2024a
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Pmet: Precise model editing in a transformer
Xiaopeng Li, Shasha Li, Shezheng Song, Jing Yang, Jun Ma, and Jie Yu. 2024b
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Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas. 2017a
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Communication-efficient learning of deep networks from decentralized data
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A robust privacy-preserving federated learning model against model poisoning attacks
Abbas Yazdinejad, Ali Dehghantanha, Hadis Karimipour, Gautam Srivastava, and Reza M Parizi. 2024 · 2024
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Locate-then-edit for multi-hop factual recall under knowledge editing
Zhuoran Zhang, Yongxiang Li, Zijian Kan, Keyuan Cheng, Lijie Hu, and Di Wang. 2024 · 2024
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