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NER

The named entity recognition (NER) involves identification of key information in the text and classification into a set of predefined categories. This includes standard entities in the text like Part of Speech (PoS) and entities like places, names etc...

Papers

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Showing 321–330 of 1729 papers

TitleStatusHype
Efficient Transformer Knowledge Distillation: A Performance Review—0
Adapt in Contexts: Retrieval-Augmented Domain Adaptation via In-Context Learning—0
Bit Cipher -- A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models—0
Understanding and Mitigating Classification Errors Through Interpretable Token Patterns—0
Use GPT-J Prompt Generation with RoBERTa for NER Models on Diagnosis Extraction of Periodontal Diagnosis from Electronic Dental Records—0
Extracting periodontitis diagnosis in clinical notes with RoBERTa and regular expression—0
GSAP-NER: A Novel Task, Corpus, and Baseline for Scholarly Entity Extraction Focused on Machine Learning Models and DatasetsCode1
SegMix: A Simple Structure-Aware Data Augmentation Method—0
Uncertainty Estimation on Sequential Labeling via Uncertainty TransmissionCode0
Universal NER: A Gold-Standard Multilingual Named Entity Recognition BenchmarkCode1
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