Improving Few-Shot Named Entity Recognition with Causal Interventions
Few-shot Named Entity Recognition (NER) systems are designed to identify new categories of entities with a limited number of labeled examples.A major challenge encountered by these systems is overfitting, particularly pronounced in comparison to tasks with ample samples.This overfitting predominantly stems from spurious correlations, a consequence