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We investigate how Large Language Models (LLMs) distinguish between memorization and generalization at the neuron level.
The perceptron: a probabilistic model for information storage and organization in the brain
Frank Rosenblatt. 1958 · 1958
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Brodmann’s’ localisation in the cerebral cortex’
Laurence J Garey. 1999 · 1999
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Transformer feed-forward layers are key-value memories
Mor Geva, Roei Schuster, Jonathan Berant, and Omer Levy. 2020 · 2012
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Towards ai-complete question answering: A set of prerequisite toy tasks
Jason Weston, Antoine Bordes, Sumit Chopra, Alexander M Rush, Bart Van Merriënboer, Armand Joulin, and Tomas Mikolov. 2015 · 2015
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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Memorization vs. generalization: Quantifying data leakage in nlp performance evaluation
Aparna Elangovan, Jiayuan He, and Karin Verspoor. 2021 · 2021
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Deduplicating training data makes language models better
Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, and Nicholas Carlini. 2021 · 2021
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Quantifying memorization across neural language models
Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, and Chiyuan Zhang. 2022 · 2022
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Towards reasoning in large language models: A survey
Jie Huang and Kevin Chen-Chuan Chang. 2022 · 2022
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Locating and editing factual associations in gpt
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022 · 2022
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Memorization without overfitting: Analyzing the training dynamics of large language models
Kushal Tirumala, Aram Markosyan, Luke Zettlemoyer, and Armen Aghajanyan. 2022 · 2022
Cited alongside, same era.
Instruction-tuning aligns llms to the human brain
Khai Loong Aw, Syrielle Montariol, Badr AlKhamissi, Martin Schrimpf, and Antoine Bosselut. 2023 · 2023
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Can llm-generated misinformation be detected?
Canyu Chen and Kai Shu. 2023 · 2023
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Truth-o-meter: Collaborating with llm in fighting its hallucinations
Boris A Galitsky. 2023 · 2023
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Teaching arithmetic to small transformers
Nayoung Lee, Kartik Sreenivasan, Jason D Lee, Kangwook Lee, and Dimitris Papailiopoulos. 2023 · 2023
Emergent and predictable memorization in large language models
Stella Biderman, Usvsn Prashanth, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, and Edward Raff. 2024 · 2024
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Unfamiliar finetuning examples control how language models hallucinate
Katie Kang, Eric Wallace, Claire Tomlin, Aviral Kumar, and Sergey Levine. 2024 · 2024
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Learning, forgetting, remembering: Insights from tracking llm memorization during training
Danny Leybzon and Corentin Kervadec. 2024 · 2024
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Inference-time intervention: Eliciting truthful answers from a language model
Kenneth Li, Oam Patel, Fernanda Viégas, Hanspeter Pfister, and Martin Wattenberg. 2024 · 2024
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Quantifying in-context reasoning effects and memorization effects in llms
Siyu Lou, Yuntian Chen, Xiaodan Liang, Liang Lin, and Quanshi Zhang. 2024 · 2024
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Semantic reconstruction of continuous language from non-invasive brain recordings
Jerry Tang, Amanda LeBel, Shailee Jain, and Alexander G Huth. 2023 · 2023
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Exploring memorization in fine-tuned language models
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Counterfactual memorization in neural language models
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Do large language models mirror cognitive language processing?
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Can llm graph reasoning generalize beyond pattern memorization?
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