Paper says localized gradients improve language-model data attribution
On the synthetic CATT benchmark, top-token negative log-odds scoring lifts ground-truth recall by 35 to 72 points.
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On the synthetic CATT benchmark, top-token negative log-odds scoring lifts ground-truth recall by 35 to 72 points.
A provenance contract audits synthetic Japanese care-handoff speech before attributing behavior to training data.
Synthetic-text source attribution collapses after rewriting and does not reliably curb model degradation.
A local learning interaction unifies data attribution, forgetting, and plasticity loss in continual updates.
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