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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 301–325 of 1729 papers

TitleStatusHype
NERCat: Fine-Tuning for Enhanced Named Entity Recognition in CatalanCode0
Generative AI for Named Entity Recognition in Low-Resource Language Nepali—0
Cross-Lingual IPA Contrastive Learning for Zero-Shot NER—0
GEMA-Score: Granular Explainable Multi-Agent Score for Radiology Report EvaluationCode0
Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition—0
Comparative Study of Zero-Shot Cross-Lingual Transfer for Bodo POS and NER Tagging Using Gemini 2.0 Flash Thinking Experimental Model—0
HILGEN: Hierarchically-Informed Data Generation for Biomedical NER Using Knowledgebases and Large Language Models—0
From Voice to Safety: Language AI Powered Pilot-ATC Communication Understanding for Airport Surface Movement Collision Risk Assessment—0
A Cooperative Multi-Agent Framework for Zero-Shot Named Entity RecognitionCode0
Iterative Auto-Annotation for Scientific Named Entity Recognition Using BERT-Based Models—0
MMRAG: Multi-Mode Retrieval-Augmented Generation with Large Language Models for Biomedical In-Context Learning—0
Data-Constrained Synthesis of Training Data for De-Identification—0
Beyond the Surface: Uncovering Implicit Locations with LLMs for Personalized Local News—0
ANCHOLIK-NER: A Benchmark Dataset for Bangla Regional Named Entity Recognition—0
Named entity recognition for Serbian legal documents: Design, methodology and dataset development—0
Beyond English: The Impact of Prompt Translation Strategies across Languages and Tasks in Multilingual LLMs—0
Claim Extraction for Fact-Checking: Data, Models, and Automated Metrics—0
TriNER: A Series of Named Entity Recognition Models For Hindi, Bengali & Marathi—0
FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual FrameworkCode0
NER4all or Context is All You Need: Using LLMs for low-effort, high-performance NER on historical texts. A humanities informed approach—0
General Embedding vs. Task-Specific Embedding: A Comparative Approach to Enhancing NLP Performance—0
Revisiting Projection-based Data Transfer for Cross-Lingual Named Entity Recognition in Low-Resource LanguagesCode0
Survey: Understand the challenges of MachineLearning Experts using Named EntityRecognition Tools—0
Academic Case Reports Lack Diversity: Assessing the Presence and Diversity of Sociodemographic and Behavioral Factors related to Post COVID-19 Condition—0
LegalGuardian: A Privacy-Preserving Framework for Secure Integration of Large Language Models in Legal Practice—0
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