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.
ArXiv abs/1911.02855
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InCTRLv2 extends InCTRL with discriminative and one-class anomaly score learning modules to achieve state-of-the-art few-shot generalist anomaly detection and segmentation across ten datasets.
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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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InCTRLv2: Generalist Residual Models for Few-Shot Anomaly Detection and Segmentation
InCTRLv2 extends InCTRL with discriminative and one-class anomaly score learning modules to achieve state-of-the-art few-shot generalist anomaly detection and segmentation across ten datasets.