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The training of modern large language models (LLMs) takes place in a regime where most training examples are seen only a few times by the model during the course of training.
Language models are few-shot learners
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · 1901
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Recognition memory for words, sentences, and pictures
Shepard, R. N. (1967) · 1967
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Fifty years of memory for names and faces: A cross-sectional approach
Bahrick, H. P., Bahrick, P. O., and Wittlinger, R. P. (1975) · 1975
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Semantic memory content in permastore: Fifty years of memory for Spanish learned in school
Bahrick, H. P. (1984) · 1984
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Retention of Spanish vocabulary over 8 years
Bahrick, H. P. and Phelphs, E. (1987) · 1987
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On the very long-term retention of knowledge acquired through formal education: Twelve years of cognitive psychology
Conway, M. A., Cohen, G., and Stanhope, N. (1991) · 1991
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On the form of forgetting
Wixted, J. T. and Ebbesen, E. B. (1991) · 1991
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Very long-term retention of a novel
Stanhope, N., Cohen, G., and Conway, M. (1993) · 1993
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One hundred years of forgetting: A quantitative description of retention
Rubin, D. C. and Wenzel, A. E. (1996) · 1996
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ROUGE: A package for automatic evaluation of summaries
Lin, C.-Y. (2004) · 2004
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Long-term retention of basic science knowledge: A review study
Custers, E. J. (2010) · 2010
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Note on the power law of forgetting
Kahana, M. J. and Adler, M. (2017) · 2017
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The secret sharer: Evaluating and testing unintended memorization in neural networks
Carlini, N., Liu, C., Erlingsson, Ú., Kos, J., and Song, D. (2019) · 2019
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Extracting training data from large language models
Carlini, N., Tramer, F., Wallace, E., Jagielski, M., Herbert-Voss, A., Lee, K., Roberts, A., Brown, T. B., Song, D., Erlingsson, U., et al. (2021) · 2021
Counterfactual memorization in neural language models
Zhang, C., Ippolito, D., Lee, K., Jagielski, M., Tramèr, F., and Carlini, N. (2021) · 2021
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Quantifying memorization across neural language models
Carlini, N., Ippolito, D., Jagielski, M., Lee, K., Tramer, F., and Zhang, C. (2022) · 2022
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Understanding transformer memorization recall through idioms
Haviv, A., Cohen, I., Gidron, J., Schuster, R., Goldberg, Y., and Geva, M. (2022) · 2022
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Preventing verbatim memorization in language models gives a false sense of privacy
Ippolito, D., Tramèr, F., Nasr, M., Zhang, C., Jagielski, M., Lee, K., Choquette-Choo, C. A., and Carlini, N. (2022) · 2022
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How BPE affects memorization in transformers
Kharitonov, E., Baroni, M., and Hupkes, D. (2021) · 2021
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McCoy, R. T., Smolensky, P., Linzen, T., Gao, J., and Celikyilmaz, A. (2021) · 2021
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Kandpal, N., Deng, H., Roberts, A., Wallace, E., and Raffel, C. (2022) · 2022
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Mallen, A., Asai, A., Zhong, V., Das, R., Hajishirzi, H., and Khashabi, D. (2022) · 2022
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Training language models to follow instructions with human feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al. (2022) · 2022
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Memorization without overfitting: Analyzing the training dynamics of large language models
Tirumala, K., Markosyan, A. H., Zettlemoyer, L., and Aghajanyan, A. (2022) · 2022
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