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Model editing is an emerging field that focuses on updating the knowledge embedded within large language models (LLMs) without extensive retraining.
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KAT: A knowledge adversarial training method for zero-order takagi-sugeno-kang fuzzy classifiers
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Investigating gender bias in language models using causal mediation analysis
Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, and Stuart M. Shieber · 2020
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Nicola De Cao, Wilker Aziz, and Ivan Titov · 2021
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Training verifiers to solve math word problems
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Baolin Peng, Michel Galley, Pengcheng He, Hao Cheng, Yujia Xie, Yu Hu, Qiuyuan Huang, Lars Liden, Zhou Yu, Weizhu Chen, and Jianfeng Gao · 2023
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Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton-Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, et al · 2023
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Easyedit: An easy-to-use knowledge editing framework for large language models
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Eva-kellm: A new benchmark for evaluating knowledge editing of llms
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Principal component analysis: A natural approach to data exploration
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Locating and editing factual associations in GPT
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov · 2022
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Fast model editing at scale
Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, and Christopher D. Manning · 2022
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Memory-based model editing at scale
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Suhang Wu, Minlong Peng, Yue Chen, Jinsong Su, and Mingming Sun · 2023
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Siren’s song in the AI ocean: A survey on hallucination in large language models
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, Longyue Wang, Anh Tuan Luu, Wei Bi, Freda Shi, and Shuming Shi · 2023
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Mquake: Assessing knowledge editing in language models via multi-hop questions
Zexuan Zhong, Zhengxuan Wu, Christopher D. Manning, Christopher Potts, and Danqi Chen · 2023
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PID control-based self-healing to improve the robustness of large language models
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Model editing harms general abilities of large language models: Regularization to the rescue
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A unified framework for model editing
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Wilke: Wise-layer knowledge editor for lifelong knowledge editing
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Zo-adamu optimizer: Adapting perturbation by the momentum and uncertainty in zeroth-order optimization
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Rethinking interpretability in the era of large language models
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Editing conceptual knowledge for large language models
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The butterfly effect of model editing: Few edits can trigger large language models collapse
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MELO: enhancing model editing with neuron-indexed dynamic lora
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A comprehensive study of knowledge editing for large language models
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On prompt-driven safeguarding for large language models
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