44 citations · 133 across the 18 of their papers we have counts for
17 papers · 1 filter
An Effective Method using Phrase Mechanism in Neural Machine Translation
Phuong Minh Nguyen, Le Minh Nguyen
Machine Translation is one of the essential tasks in Natural Language Processing (NLP), which has massive applications in real life as well as contributing to other tasks in the NL…
Improving Vietnamese Legal Question--Answering System based on Automatic Data Enrichment
Thi-Hai-Yen Vuong, Ha-Thanh Nguyen, Quang-Huy Nguyen +2
Question answering (QA) in law is a challenging problem because legal documents are much more complicated than normal texts in terms of terminology, structure, and temporal and log…
Law to Binary Tree -- An Formal Interpretation of Legal Natural Language
Ha-Thanh Nguyen, Vu Tran, Ngoc-Cam Le +4
Knowledge representation and reasoning in law are essential to facilitate the automation of legal analysis and decision-making tasks. In this paper, we propose a new approach based…
Transformer-based Approaches for Legal Text Processing
Ha-Thanh Nguyen, Minh-Phuong Nguyen, Thi-Hai-Yen Vuong +6
In this paper, we introduce our approaches using Transformer-based models for different problems of the COLIEE 2021 automatic legal text processing competition. Automated processin…
HYDRA -- Hyper Dependency Representation Attentions
Ha-Thanh Nguyen, Vu Tran, Tran-Binh Dang +3
Attention is all we need as long as we have enough data. Even so, it is sometimes not easy to determine how much data is enough while the models are becoming larger and larger. In…
Sublanguage: A Serious Issue Affects Pretrained Models in Legal Domain
Ha-Thanh Nguyen, Le-Minh Nguyen
Legal English is a sublanguage that is important for everyone but not for everyone to understand. Pretrained models have become best practices among current deep learning approache…
Improving Multilingual Neural Machine Translation For Low-Resource Languages: French,English - Vietnamese
Thi-Vinh Ngo, Phuong-Thai Nguyen, Thanh-Le Ha +2
Prior works have demonstrated that a low-resource language pair can benefit from multilingual machine translation (MT) systems, which rely on many language pairs' joint training. T…
Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation
Thi-Vinh Ngo, Thanh-Le Ha, Phuong-Thai Nguyen +1
Among the six challenges of neural machine translation (NMT) coined by (Koehn and Knowles, 2017), rare-word problem is considered the most severe one, especially in translation of…
How Transformer Revitalizes Character-based Neural Machine Translation: An Investigation on Japanese-Vietnamese Translation Systems
Thi-Vinh Ngo, Thanh-Le Ha, Phuong-Thai Nguyen +1
While translating between East Asian languages, many works have discovered clear advantages of using characters as the translation unit. Unfortunately, traditional recurrent neural…
An empirical evaluation of AMR parsing for legal documents
Sinh Vu Trong, Minh Nguyen Le
Many approaches have been proposed to tackle the problem of Abstract Meaning Representation (AMR) parsing, helps solving various natural language processing issues recently. In our…
Dual Latent Variable Model for Low-Resource Natural Language Generation in Dialogue Systems
Van-Khanh Tran, Le-Minh Nguyen
Recent deep learning models have shown improving results to natural language generation (NLG) irrespective of providing sufficient annotated data. However, a modest training data m…
Adversarial Domain Adaptation for Variational Neural Language Generation in Dialogue Systems
Van-Khanh Tran, Le-Minh Nguyen
Domain Adaptation arises when we aim at learning from source domain a model that can per- form acceptably well on a different target domain. It is especially crucial for Natural La…
Combining Advanced Methods in Japanese-Vietnamese Neural Machine Translation
Thi-Vinh Ngo, Thanh-Le Ha, Phuong-Thai Nguyen +1
Neural machine translation (NMT) systems have recently obtained state-of-the art in many machine translation systems between popular language pairs because of the availability of d…
ConvAMR: Abstract meaning representation parsing for legal document
Lai Dac Viet, Vu Trong Sinh, Nguyen Le Minh +1
Convolutional neural networks (CNN) have recently achieved remarkable performance in a wide range of applications. In this research, we equip convolutional sequence-to-sequence (se…
Neural-based Natural Language Generation in Dialogue using RNN Encoder-Decoder with Semantic Aggregation
Van-Khanh Tran, Le-Minh Nguyen
Natural language generation (NLG) is an important component in spoken dialogue systems. This paper presents a model called Encoder-Aggregator-Decoder which is an extension of an Re…
Semantic Refinement GRU-based Neural Language Generation for Spoken Dialogue Systems
Van-Khanh Tran, Le-Minh Nguyen
Natural language generation (NLG) plays a critical role in spoken dialogue systems. This paper presents a new approach to NLG by using recurrent neural networks (RNN), in which a g…
Natural Language Generation for Spoken Dialogue System using RNN Encoder-Decoder Networks
Van-Khanh Tran, Le-Minh Nguyen
Natural language generation (NLG) is a critical component in a spoken dialogue system. This paper presents a Recurrent Neural Network based Encoder-Decoder architecture, in which a…