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When Is Benchmark Contamination Detectable? Information Limits and Power-Calibrated Audits

arXiv:2608.07914v1 Announce Type: new Abstract: Behavioral contamination detectors can return 'no evidence' either because a benchmark is clean or because the audit has little power. We formalize this

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model-releasesarxiv-cs-ai

arXiv:2608.07914v1 Announce Type: new Abstract: Behavioral contamination detectors can return "no evidence" either because a benchmark is clean or because the audit has little power. We formalize this distinction for a benchmark in which an unknown fraction alpha of items was seen during training. With matched clean and seen controls, the behavioral channel is the sparse mixture Q_alpha = (1 - alpha) P_0 + alpha P_1, and an exact second-moment argument shows that detectability is governed by alpha * rho * sqrt(m), where rho^2 = chi^2(P_1 || P_0) measures behavioral separability. Any scalar detector reduces to its efficacy, ef = |E_1 f - E_0 f| / sqrt(Var_0(f)) paraphrase > surface, in which the apparent answer-only signal is explained by baseline drift. We report the audit contract and its failures together: a non-rejection is interpretable only alongside the efficacy, budget, and validity gates that produced it.

Source: arXiv cs.AI | 2026-08-11

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