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Humans rarely learn one fact in isolation.
Explanatory coherence
Paul Thagard. 1989 · 1989
Earlier work this paper cites.
A Coherence Model of Cognitive Consistency: Dynamics of Attitude Change During the Persian Gulf War
Barbara A. Spellman, Jodie B. Ullman, and Keith J. Holyoak. 1993 · 1993
Earlier work this paper cites.
Bidirectional Reasoning in Decision Making by Constraint Satisfaction
Keith J Holyoak and Dan Simon. 1999 · 1999
Earlier work this paper cites.
Intuitive theories
Tobias Gerstenberg and Joshua B. Tenenbaum. 2017 · 2017
Earlier work this paper cites.
Editing Factual Knowledge in Language Models
Nicola De Cao, Wilker Aziz, and Ivan Titov. 2021 · 2021
Earlier work this paper cites.
Knowledge Neurons in Pretrained Transformers
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Earlier work this paper cites.
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Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022 · 2022
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The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"
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Earlier work this paper cites.
Aging with grace: Lifelong model editing with discrete key-value adaptors
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Earlier work this paper cites.
Methods for Measuring, Updating, and Visualizing Factual Beliefs in Language Models
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The Sol Supercomputer at Arizona State University
Douglas M. Jennewein, Johnathan Lee, Chris Kurtz, Will Dizon, Ian Shaeffer, Alan Chapman, Alejandro Chiquete, Josh Burks, Amber Carlson, Natalie Mason, Arhat Kobwala, Thirugnanam Jagadeesan, Praful Barghav, Torey Battelle, Rebecca Belshe, Debra McCaffrey, Marisa Brazil, Chaitanya Inumella, Kirby Kuznia, Jade Buzinski, Sean Dudley, Dhruvil Shah, Gil Speyer, and Jason Yalim. 2023 · 2023
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Large Language Models Struggle to Learn Long-Tail Knowledge
Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, and Colin Raffel. 2023 · 2023
Modeling and leveraging intuitive theories to improve vaccine attitudes
Derek Powell, Kara Weisman, and Ellen M Markman. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Can We Edit Factual Knowledge by In-Context Learning?
Ce Zheng, Lei Li, Qingxiu Dong, Yuxuan Fan, Zhiyong Wu, Jingjing Xu, and Baobao Chang. 2023 · 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 · 2023
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Evaluating the ripple effects of knowledge editing in language models
Roi Cohen, Eden Biran, Ori Yoran, Amir Globerson, and Mor Geva. 2024 · 2024
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When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories
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Mass-Editing Memory in a Transformer
Kevin Meng, Arnab Sen Sharma, Alex Andonian, Yonatan Belinkov, and David Bau. 2023 · 2023
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Emptying the Ocean with a Spoon: Should We Edit Models?
Yuval Pinter and Michael Elhadad. 2023 · 2023
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Fast model editing at scale
Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, and Christopher D Manning. 2022a
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Memory-Based Model Editing at Scale
Eric Mitchell, Charles Lin, Antoine Bosselut, Christopher D. Manning, and Chelsea Finn. 2022b
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Easyedit: An easy-to-use knowledge editing framework for large language models
Peng Wang, Ningyu Zhang, Xin Xie, Yunzhi Yao, Bozhong Tian, Mengru Wang, Zekun Xi, Siyuan Cheng, Kangwei Liu, Guozhou Zheng, et al. 2023a
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Infini-gram: Scaling unbounded n-gram language models to a trillion tokens
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Dolma: An open corpus of three trillion tokens for language model pretraining research
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