A meta-learning framework with cross-domain episode sampling achieves higher anomaly detection AUC and F1 than fine-tuned BERT and one-class SVM on SMS spam, COVID-19 fake news, and hate speech tasks.
If $A=B$ (intra-domain case), ensure that support+query sampling includes at most $n_a$ anomalies and majority normal, as per the anomaly rate
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Anomaly Detection in Human Language via Meta-Learning: A Few-Shot Approach
A meta-learning framework with cross-domain episode sampling achieves higher anomaly detection AUC and F1 than fine-tuned BERT and one-class SVM on SMS spam, COVID-19 fake news, and hate speech tasks.