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Which Influence Are We Estimating? The Role of Counterfactual Specifications in Data Attribution
Estimating the influence of training examples on model behavior is essential for data debugging, valuation, and attribution. Existing influence estimators often produce incompatible rankings, which are commonly ascribed to approximation error. We argue that a more fundamental source of disagreement
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