Monolingual versus Multilingual BERTology for Vietnamese Extractive Multi-Document Summarization

FOS: Computer and information sciences Computer Science - Computation and Language Artificial Intelligence (cs.AI) Computer Science - Artificial Intelligence 0202 electrical engineering, electronic engineering, information engineering 02 engineering and technology 01 natural sciences Computation and Language (cs.CL) 0105 earth and related environmental sciences
DOI: 10.48550/arxiv.2108.13741 Publication Date: 2021-01-01
ABSTRACT
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 on multi-document. 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.
SUPPLEMENTAL MATERIAL
Coming soon ....
REFERENCES ()
CITATIONS ()
EXTERNAL LINKS
PlumX Metrics
RECOMMENDATIONS
FAIR ASSESSMENT
Coming soon ....
JUPYTER LAB
Coming soon ....