AWhat changed
Combines model-output linearization, random-projected gradient features, approximate logistic influence and model ensembling to estimate data attribution, evaluating subset counterfactual predictions with a rank-correlation score.
Scientific scope
Combines model-output linearization, random-projected gradient features, approximate logistic influence and model ensembling to estimate data attribution, evaluating subset counterfactual predictions with a rank-correlation score. Linearization, dropping curvature factors and ensembling are approximations, not exact neural retraining or causal truth. Speed/quality findings are source-specific empirical comparisons; fixed-projection preservation does not guarantee full attribution correctness. First three authors explicitly equal.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Linearization, dropping curvature factors and ensembling are approximations, not exact neural retraining or causal truth. Speed/quality findings are source-specific empirical comparisons; fixed-projection preservation does not guarantee full attribution correctness. First three authors explicitly equal.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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