Advancing the Interests of Authors Who Want to Serve the Public Good
On Memorization
“We say that a model has “memorized” a piece of training data when (1) it is possible to reconstruct from the model (2) a (near-)exact copy of (3) a substantial portion of (4) that specific piece of training data. We distinguish memorization from “extraction” (in which a user intentionally causes a model to generate a (near-)exact copy), from “regurgitation” (in which a model generates a (near-)exact copy, regardless of the user’s intentions), and from “reconstruction” (in which the (near-)exact copy can be obtained from the model by any means, not necessarily the ordinary generation process).” A. Feder Cooper and James…
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