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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.25492 |
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| _version_ | 1866913161287827456 |
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| author | Li, Yanhang Fan, Zhichao Zhuang, Zexin |
| author_facet | Li, Yanhang Fan, Zhichao Zhuang, Zexin |
| contents | Pairwise model comparisons drawn from foundation-model benchmarks ("A is safer than B") are read as quantitative verdicts but hinge on harness choices benchmark papers under-specify. We close one theory-benchmark loop on this primitive: a finite-envelope proposition tying a measurable pairwise-disagreement rate to whether the strict ordering admits a configuration-pair reversal, paired with a commit-stamped evaluation protocol that operationalises it on widely cited alignment benchmarks. On every benchmark we test, configuration choice alone can flip the pairwise verdict; the proposition isolates this strict-reversal failure mode. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_25492 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SafetyRepro: Configuration-Conditional Rank Instability on Alignment Benchmarks Li, Yanhang Fan, Zhichao Zhuang, Zexin Machine Learning Pairwise model comparisons drawn from foundation-model benchmarks ("A is safer than B") are read as quantitative verdicts but hinge on harness choices benchmark papers under-specify. We close one theory-benchmark loop on this primitive: a finite-envelope proposition tying a measurable pairwise-disagreement rate to whether the strict ordering admits a configuration-pair reversal, paired with a commit-stamped evaluation protocol that operationalises it on widely cited alignment benchmarks. On every benchmark we test, configuration choice alone can flip the pairwise verdict; the proposition isolates this strict-reversal failure mode. |
| title | SafetyRepro: Configuration-Conditional Rank Instability on Alignment Benchmarks |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2605.25492 |