Extractable Memorization From First Principles

Formal framework for valid extractable memorization claims in LLMs

A new arXiv preprint proposes a principled methodology for making valid extractable memorization claims about LLMs, addressing both over- and under-statement problems in prior work. The core contribution is a 'matched comparison' approach that measures generation probabilities of training sequences against comparable non-training sequences to establish a calibrated baseline for predictability. Two formalizations are offered: a conformal test for population-level claims and a census method for single-document claims. Applied to OLMo 2 32B on Wikipedia and Llama 3.1 70B on books, the framework reveals significant false-positive rates in naive extraction studies and supports memorization claims at probability thresholds as low as 1e-27.