Demystifying Verbatim Memorization in Large Language Models

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Abstracting causal models

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The secret sharer: Evaluating and testing unintended memorization in neural networks

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Does learning require memorization? A short tale about a long tail

Vitaly Feldman. 2020 · 2020

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What neural networks memorize and why: Discovering the long tail via influence estimation

Vitaly Feldman and Chiyuan Zhang. 2020 · 2020

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The Pile: An 800GB dataset of diverse text for language modeling

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Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, Shawn Presser, and Connor Leahy. 2020 · 2020

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Investigating gender bias in language models using causal mediation analysis

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When is memorization of irrelevant training data necessary for high-accuracy learning?

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Extracting training data from large language models

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Similarity and matching of neural network representations

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Causal abstractions of neural networks

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Transformer feed-forward layers are key-value memories

Mor Geva, Roei Schuster, Jonathan Berant, and Omer Levy. 2021 · 2021

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On memorization in probabilistic deep generative models

Gerrit van den Burg and Chris Williams. 2021 · 2021

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Knowledge neurons in pretrained transformers

Damai Dai, Li Dong, Yaru Hao, Zhifang Sui, Baobao Chang, and Furu Wei. 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 H. Markosyan, Luke Zettlemoyer, and Armen Aghajanyan. 2022 · 2022

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Quantifying memorization across neural language models

Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, and Chiyuan Zhang. 2023 · 2023

Scalable extraction of training data from (production) language models

Original

Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, and Katherine Lee. 2023 · 2023

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Scan and snap: Understanding training dynamics and token composition in 1-layer transformer

Yuandong Tian, Yiping Wang, Beidi Chen, and Simon Shaolei Du. 2023 · 2023

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Neurons in large language models: Dead, n-gram, positional

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Elena Voita, Javier Ferrando, and Christoforos Nalmpantis. 2023 · 2023

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Counterfactual memorization in neural language models

Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramèr, and Nicholas Carlini. 2023 · 2023

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Physics of language models: Part 3.3, knowledge capacity scaling laws