Named Entity Recognition In Vietnamese
5 papers with code • 2 benchmarks • 1 datasets
Most implemented papers
A Deep Neural Network Model for the Task of Named Entity Recognition
One of the most important factors which directly and significantly affects the quality of the neural sequence labeling is the selection and encoding the input features to generate rich semantic and grammatical representation vectors.
Attentive Neural Network for Named Entity Recognition in Vietnamese
We propose an attentive neural network for the task of named entity recognition in Vietnamese.
COVID-19 Named Entity Recognition for Vietnamese
The current COVID-19 pandemic has lead to the creation of many corpora that facilitate NLP research and downstream applications to help fight the pandemic.
ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation
In this work, we perform exhaustive experiments on both Vietnamese Abstractive Summarization and Named Entity Recognition, validating the performance of ViT5 against many other pretrained Transformer-based encoder-decoder models.
ViHealthBERT: Pre-trained Language Models for Vietnamese in Health Text Mining
We introduce ViHealthBERT, the first domain-specific pre-trained language model for Vietnamese healthcare.