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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 1–25 of 1729 papers

TitleStatusHype
Flippi: End To End GenAI Assistant for E-Commerce—0
Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language ModelsCode0
Improving Named Entity Transcription with Contextual LLM-based Revision—0
Better Semi-supervised Learning for Multi-domain ASR Through Incremental Retraining and Data Filtering—0
Efficient Data Selection for Domain Adaptation of ASR Using Pseudo-Labels and Multi-Stage Filtering—0
Label-Guided In-Context Learning for Named Entity RecognitionCode1
EL4NER: Ensemble Learning for Named Entity Recognition via Multiple Small-Parameter Large Language Models—0
Named Entity Recognition in Historical Italian: The Case of Giacomo Leopardi's ZibaldoneCode0
RetrieveAll: A Multilingual Named Entity Recognition Framework with Large Language Models—0
FiLLM -- A Filipino-optimized Large Language Model based on Southeast Asia Large Language Model (SEALLM)—0
Does Synthetic Data Help Named Entity Recognition for Low-Resource Languages?—0
Towards DS-NER: Unveiling and Addressing Latent Noise in Distant AnnotationsCode0
Automated Detection of Clinical Entities in Lung and Breast Cancer Reports Using NLP Techniques—0
LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs—0
A Comparative Analysis of Static Word Embeddings for HungarianCode0
Development of a WAZOBIA-Named Entity Recognition System—0
Symbol-based entity marker highlighting for enhanced text mining in materials science with generative AI—0
Logits-Constrained Framework with RoBERTa for Ancient Chinese NER—0
Positional Attention for Efficient BERT-Based Named Entity Recognition—0
VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural LanguageCode0
Zero-Shot Document-Level Biomedical Relation Extraction via Scenario-based Prompt Design in Two-Stage with LLM—0
Natural Language Processing tools for Pharmaceutical Manufacturing Information Extraction from PatentsCode0
Methods for Recognizing Nested TermsCode0
LLMs as Data Annotators: How Close Are We to Human Performance—0
EIoU-EMC: A Novel Loss for Domain-specific Nested Entity Recognition—0
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