DynamicNER is a dynamic-categorization multilingual NER dataset with 155 entity types paired with CascadeNER, a two-stage lightweight LLM method claiming higher fine-grained accuracy.
Ensemble deep learning: A review
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SDNGuardStack ensemble learning model reports 99.98% accuracy and 0.9998 Cohen's kappa on the InSDN dataset for SDN intrusion detection while providing SHAP-based explanations.
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DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition
DynamicNER is a dynamic-categorization multilingual NER dataset with 155 entity types paired with CascadeNER, a two-stage lightweight LLM method claiming higher fine-grained accuracy.
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SDNGuardStack: An Explainable Ensemble Learning Framework for High-Accuracy Intrusion Detection in Software-Defined Networks
SDNGuardStack ensemble learning model reports 99.98% accuracy and 0.9998 Cohen's kappa on the InSDN dataset for SDN intrusion detection while providing SHAP-based explanations.