arXiv cs.AI
· Papers
In-Run Data Shapley for Adam Optimizer
arXiv:2602.00329v4 Announce Type: replace-cross Abstract: Reliable data attribution is essential for mitigating bias and reducing computational waste in modern machine learning, with the Shapley value serving as the theoretical gold standard. While recent "In-Run" methods bypass the prohibitive cost of retraining by es