Xuan-Dung Doan


Multi Graph Neural Network for Extractive Long Document Summarization
Xuan-Dung Doan | Le-Minh Nguyen | Khac-Hoai Nam Bui
Proceedings of the 29th International Conference on Computational Linguistics

Heterogeneous Graph Neural Networks (HeterGNN) have been recently introduced as an emergent approach for extracting document summarization (EDS) by exploiting the cross-relations between words and sentences. However, applying HeterGNN for long documents is still an open research issue. One of the main majors is the lacking of inter-sentence connections. In this regard, this paper exploits how to apply HeterGNN for long documents by building a graph on sentence-level nodes (homogeneous graph) and combine with HeterGNN for capturing the semantic information in terms of both inter and intra-sentence connections. Experiments on two benchmark datasets of long documents such as PubMed and ArXiv show that our method is able to achieve state-of-the-art results in this research field.


A Joint Deep Contextualized Word Representation for Deep Biaffine Dependency Parsing
Xuan-Dung Doan
Proceedings of the 7th International Workshop on Vietnamese Language and Speech Processing


Effectiveness of Character Language Model for Vietnamese Named Entity Recognition
Xuan-Dung Doan | Trung-Thanh Dang | Le-Minh Nguyen
Proceedings of the 32nd Pacific Asia Conference on Language, Information and Computation