From Training Exposure to Membership Evidence: A Controlled Study of OLMo 2
A controlled membership-inference study on OLMo 2 with verified training data provides a stronger evidence standard for copyright and data-privacy audits of LLMs than retrospective approaches.
Summary written by editorial AI · Source link below
arXiv:2610.41732v1 Announce Type: new Abstract: Whether a language model was trained on a document matters for copyright, privacy, and benchmark contamination. Yet most membership-inference (MI) evaluations on language models collect members and non-members after the fact, so success may reflect distribution shift and failure is inconclusive. We re-ran OLMo 2 1B's official 50-billion-token mid-training stage, replacing selected training chunks with documents from 7,814 pairs matched on domain a
Editorial Analysis
Enterprises procuring or fine-tuning LLMs face growing copyright and privacy scrutiny; rigorous membership-inference methods strengthen due-diligence evidence.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
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