Dec 24, 2021 · We formulate a notion of counterfactual memorization which characterizes how a model's predictions change if a particular document is omitted ...
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Nov 16, 2022 · We formulate a notion of counterfactual memorization, which characterizes how a model's predictions change if a particular document is omitted during training.
We formulate a notion of counterfactual memorization which characterizes how a model's predictions change if a particular document is omitted during training.
May 30, 2024 · We formulate a notion of counterfactual memorization which characterizes how a model's predictions change if a particular document is omitted ...
This work identifies and study counterfactually-memorized training examples in standard text datasets and estimates the influence of each memorized training ...
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Oct 13, 2023 · Modern neural language models that are widely used in various NLP tasks risk memorizing sensitive information from their training data.
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We identify and study counterfactually-memorized training examples in standard text datasets. We further estimate the influence of each training example on the ...
Jan 10, 2022 · More formally, a training example x is counterfactually memorized when the model predicts x accurately if and only if the model was trained on x ...
Jul 19, 2022 · Counterfactual Memorization. Zhang, et al., Counterfactual Memorization in Neural Language Models, arxiv, 2022. Page 19. Counterfactual ...
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