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Named Entity Recognition

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TitleStatusHype
Advancing Italian Biomedical Information Extraction with Transformers-based Models: Methodological Insights and Multicenter Practical Application—0
Multilingual Clinical NER: Translation or Cross-lingual Transfer?—0
TKDP: Threefold Knowledge-enriched Deep Prompt Tuning for Few-shot Named Entity RecognitionCode0
Skill over Scale: The Case for Medium, Domain-Specific Models for SE—0
Transformer-Based UNet with Multi-Headed Cross-Attention Skip Connections to Eliminate Artifacts in Scanned Documents—0
bgGLUE: A Bulgarian General Language Understanding Evaluation BenchmarkCode0
Impact of translation on biomedical information extraction from real-life clinical notes—0
Data-Efficient French Language Modeling with CamemBERTa—0
Learning Transformer ProgramsCode1
ACLM: A Selective-Denoising based Generative Data Augmentation Approach for Low-Resource Complex NERCode1
Examining risks of racial biases in NLP tools for child protective services—0
Machine Learning Approach for Cancer Entities Association and Classification—0
A Multilingual Evaluation of NER Robustness to Adversarial Inputs—0
W-procer: Weighted Prototypical Contrastive Learning for Medical Few-Shot Named Entity Recognition—0
E-NER: Evidential Deep Learning for Trustworthy Named Entity RecognitionCode1
Extrinsic Factors Affecting the Accuracy of Biomedical NER—0
ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER—0
Complementary and Integrative Health Lexicon (CIHLex) and Entity Recognition in the Literature—0
PromptNER: Prompt Locating and Typing for Named Entity RecognitionCode1
People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts—0
Automatic Emotion Experiencer Recognition—0
Jointprop: Joint Semi-supervised Learning for Entity and Relation Extraction with Heterogeneous Graph-based Propagation—0
PromptNER: Prompting For Named Entity Recognition—0
Automated Refugee Case Analysis: An NLP Pipeline for Supporting Legal PractitionersCode0
Prompting Large Language Models for Counterfactual Generation: An Empirical Study—0
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