• benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.
• open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.

Influence-function attribution only holds if you can verify the model actually trained on the documents you are scoring, which is why the study required a fully open stack, not just open weights.

• articleolmo-eval: An evaluation workbench for the model development loopallenai.org
• articleModular LLMs at scale: how FlexOlmo is helping to pool national expertise without pooling sensitive dataallenai.org
• articleWhen a model reads a drug's class from its name—not its knowledgeallenai.org

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