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Named Entity Recognition

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TitleStatusHype
ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPTCode2
Foresight -- Generative Pretrained Transformer (GPT) for Modelling of Patient Timelines using EHRsCode2
Named Entity Recognition in Twitter: A Dataset and Analysis on Short-Term Temporal ShiftsCode2
T-NER: An All-Round Python Library for Transformer-based Named Entity RecognitionCode2
Language Modelling with PixelsCode2
TweetNLP: Cutting-Edge Natural Language Processing for Social MediaCode2
Decomposed Meta-Learning for Few-Shot Named Entity RecognitionCode2
BERN2: an advanced neural biomedical named entity recognition and normalization toolCode2
Sensitive Data Detection with High-Throughput Neural Network Models for Financial InstitutionsCode2
MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual TransferCode2
FLAT: Chinese NER Using Flat-Lattice TransformerCode2
CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for ChineseCode2
Label-Guided In-Context Learning for Named Entity RecognitionCode1
GLiNER-BioMed: A Suite of Efficient Models for Open Biomedical Named Entity RecognitionCode1
Multimodal LLMs for OCR, OCR Post-Correction, and Named Entity Recognition in Historical DocumentsCode1
Small Language Model Makes an Effective Long Text ExtractorCode1
Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training DataCode1
ITER: Iterative Transformer-based Entity Recognition and Relation ExtractionCode1
Evaluating Named Entity Recognition Using Few-Shot Prompting with Large Language ModelsCode1
Multi-Grained Query-Guided Set Prediction Network for Grounded Multimodal Named Entity RecognitionCode1
DANIEL: A fast Document Attention Network for Information Extraction and Labelling of handwritten documentsCode1
Statements: Universal Information Extraction from Tables with Large Language Models for ESG KPIsCode1
Retrieval Augmented Instruction Tuning for Open NER with Large Language ModelsCode1
Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity RecognitionCode1
Advancing Grounded Multimodal Named Entity Recognition via LLM-Based Reformulation and Box-Based SegmentationCode1
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