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
AUTHORS (4)
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.
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