Analysis of Transfer Learning for Named Entity Recognition in South ...

Cross Lingual Named Entity Recognition using Deep Learning

implementation of cross-lingual transfer learning in named entity recognition (NER) ... The study Transfer Learning for Multilingual Tasks: A ...

MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity ...

We create the largest human-annotated NER dataset for 20 African languages, and we study the behavior of state-of-the-art cross-lingual transfer ...

Recent Advances in Named Entity Recognition - arXiv

In addition, we discuss reinforcement learning and graph-based approaches, highlighting their role in enhancing NER performance. Second, we ...

Enhancing Named Entity Recognition in Low-Resource Dravidian ...

In this study, we explore methods to enhance NER performance in these low-resource Indian languages using multilingual learning and transfer learning techniques ...

Label-Aware Double Transfer Learning for Cross-Specialty Medical ...

We study the problem of named entity recognition (NER) from electronic medical records, which is one of the most fundamental and critical problems for ...

kaisugi/entity-related-papers - GitHub

NER · Style Transfer as Data Augmentation: A Case Study on Named Entity Recognition · SetGNER: General Named Entity Recognition as Entity Set Generation ...

Deep learning-based methods for natural hazard named entity ...

A deep learning method for natural hazard named entity recognition can automatically mine text features and reduce the dependence on manual ...

MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity ...

Named entity recognition in a south african context. Jacob Devlin, Ming-Wei ... we make use for determining the best transfer lan- guages. D Error Analysis of NER.

Enhancement of Named Entity Recognition in Low-Resource ... - OUCI

This surpassed the macro f1 scores of the RoBERTa-Urdu-small (0.884%), BERT-large-cased (0.916%), and BERT-base-cased (0.908%) models. Additionally, our neural ...

Transfer Learning for Named-Entity Recognition with Neural Networks

Recent approaches based on artificial neural networks (ANNs) have shown promising results for named-entity recognition (NER).

Multi-Task Transfer Learning for Fine-Grained Named Entity ...

Can we solve NER (detection and classification) with 7,000+ types in a generic fashion? Page 3. Challenge 1: Lack of Training Data. Silver-standard dataset.

On the hidden negative transfer in sequential Transfer Learning for ...

Our experiments on three NLP tasks (Part-Of-Speech tagging (POS), Chunking. Page 3. 141. (CK) and Named Entity recognition (NER)) reveal.

Combining Contextualized Embeddings and Prior Knowledge for ...

Background: Named entity recognition (NER) is a key step in clinical natural language processing (NLP). Traditionally, rule-based systems ...

Improving large language models for clinical named entity ...

Early clinical NER systems often depend on predefined lexical resources and syntactic/semantic rules derived from extensive manual analysis of ...

Dual Contrastive Learning for Cross-Domain Named Entity ...

Benefiting many information retrieval applications, named entity recognition (NER) has shown impressive progress. Recently, there has been a ...

Zero-Shot Transfer Learning using Affix and Correlated Cross ...

Furthermore, our NER best performance was achieved using canonically correlated cross-lingual embeddings with Conditional Random Fields as the training model ( ...

A pre-training and self-training approach for biomedical named ...

In this study, we build upon previous work that explores how to effectively leverage transfer learning for biomedical NER. [32] showed that pre- ...

Investigating Transformer Models' Zero-Shot Cross Lingual Transfer ...

... learning using Urdu named entity recognition. The poor ... In Proceedings of the IJCNLP-08 Workshop on Named Entity Recognition for South and South.

Cross-Lingual Transfer Learning for Medical Named Entity ...

In medical domain, Named Entity Recognition is pivotal for many downstream tasks, such as medical entity linking and clinical decision support ...

Deep learning-based methods for natural hazard named entity ...

A deep learning method for natural hazard named entity recognition can automatically mine text features and reduce the dependence on manual rules. This paper ...