DeMix diagnoses mixed error types in training data via influence-vector-based multi-label classification with an intervention strategy, reporting 22.61% F1 gain and 9.32% downstream improvement on 11 tasks.
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DeMix: Debugging Training Data with Mixed Data Error Types by Investigating Influence Vectors
DeMix diagnoses mixed error types in training data via influence-vector-based multi-label classification with an intervention strategy, reporting 22.61% F1 gain and 9.32% downstream improvement on 11 tasks.