Feb 15, 2022 · Memorization significantly grows as we increase (1) the capacity of a model, (2) the number of times an example has been duplicated, and (3) the ...
Feb 1, 2023 · Memorization significantly grows as we increase (1) the capacity of a model, (2) the number of times an example has been duplicated, and (3) the ...
[PDF] Quantifying Memorization Across Neural Language Models
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This work finds that memorization in LMs is more prevalent than previously believed and will likely get worse as models continues to scale.
Mar 6, 2023 · This paper addresses both of the above open questions by comprehensively quantifying memorization across three families of neural language ...
Our main repository provides the prefixes and model continuations which we used in our analysis of memorization in large language models. Tip.
Memorization significantly grows as we increase (1) the capacity of a model, (2) the number of times an example has been duplicated, and (3) the number of ...
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Jul 24, 2024 · Bibliographic details on Quantifying Memorization Across Neural Language Models.
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Posted: Mar 22, 2023
Posted: Mar 22, 2023
Nov 2, 2023 · Quantifying Memorization Across Neural Language Models showed that GPT-J memorized at least 1% of its training set. Preventing Verbatim ...
This quantifies the model's memorization of training data and its capability for directed reconstruction from memoriza- tion.
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