Metadata Predictability Is Not Evidence Dependence: An Intervention-Based Audit for Weak-Label Benchmarks
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Computer Science > Computation and Language
Title:Metadata Predictability Is Not Evidence Dependence: An Intervention-Based Audit for Weak-Label Benchmarks
Abstract:We study a protocol-level test for weak-label benchmarks: whether benchmark outputs change when the provided evidence is intervened on. Metadata-only shortcut checks answer a different question, namely whether outputs are predictable from metadata priors. We therefore combine a metadata statistic, the Metadata Prior Dominance Score (MPDS), with an evidence-intervention statistic, {\Delta}Evi, measuring sensitivity to evidence identity under cross-item shuffling. Synthetic HotpotQA gives a constructed counterexample to metadata-only screening: MPDS is only moderate (0.643), yet {\Delta}Evi is zero. Stronger-reader reruns show why calibration belongs in the test procedure: SNLI shows a calibration reversal, reconstructed HotpotQA occupies a question-dominant warning region, and FEVER is a strongly evidence-sensitive positive control across four transformers. The practical lesson is simple: benchmark audits should report metadata-only screening, evidence intervention, and reader-strength calibration together.
| Comments: | 5 pages, 1 figure, 1 table. Accepted at ICML 2026 Workshop on Hypothesis Testing |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2605.23701 [cs.CL] |
| (or arXiv:2605.23701v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2605.23701
arXiv-issued DOI via DataCite (pending registration)
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