Stop AI scientists grading their own homework: CrossAudit forces a rival-vendor reviewer
AI scientists usually have their work reviewed by an agent from the same model family, and evaluators are known to favor their own generations. CrossAudit's protocol makes every increment audited instead by a different vendor against a human-written, versioned rulebook, with verdicts and disputes committed to git for anyone to replay. A cross-vendor audit of the paper itself voided its own trial's blinding. Two vendors read the same rulebook differently, though neither proved better.