Monolingual versus Multilingual BERTology for Vietnamese Extractive Multi-Document Summarization

08/31/2021
by   Huy To Quoc, et al.
0

Recent researches have demonstrated that BERT shows potential in a wide range of natural language processing tasks. It is adopted as an encoder for many state-of-the-art automatic summarizing systems, which achieve excellent performance. However, so far, there is not much work done for Vietnamese. In this paper, we showcase how BERT can be implemented for extractive text summarization in Vietnamese. We introduce a novel comparison between different multilingual and monolingual BERT models. The experiment results indicate that monolingual models produce promising results compared to other multilingual models and previous text summarizing models for Vietnamese.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/19/2022

Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi

Transformers are the most eminent architectures used for a vast range of...
research
07/22/2021

Evaluation of contextual embeddings on less-resourced languages

The current dominance of deep neural networks in natural language proces...
research
07/27/2021

gaBERT – an Irish Language Model

The BERT family of neural language models have become highly popular due...
research
02/25/2020

BERT Can See Out of the Box: On the Cross-modal Transferability of Text Representations

Pre-trained language models such as BERT have recently contributed to si...
research
02/22/2021

RUBERT: A Bilingual Roman Urdu BERT Using Cross Lingual Transfer Learning

In recent studies, it has been shown that Multilingual language models u...
research
04/04/2023

San-BERT: Extractive Summarization for Sanskrit Documents using BERT and it's variants

In this work, we develop language models for the Sanskrit language, name...

Please sign up or login with your details

Forgot password? Click here to reset