Search Results for author: Le-Minh Nguyen

Found 22 papers, 6 papers with code

Multi Graph Neural Network for Extractive Long Document Summarization

1 code implementation COLING 2022 Xuan-Dung Doan, Le-Minh Nguyen, Khac-Hoai Nam Bui

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.

Document Summarization

Improving Multilingual Neural Machine Translation For Low-Resource Languages: French, English - Vietnamese

no code implementations loresmt (AACL) 2020 Thi-Vinh Ngo, Phuong-Thai Nguyen, Thanh-Le Ha, Khac-Quy Dinh, Le-Minh Nguyen

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.

Machine Translation Translation +1

Transformer-based Approaches for Legal Text Processing

no code implementations13 Feb 2022 Ha-Thanh Nguyen, Minh-Phuong Nguyen, Thi-Hai-Yen Vuong, Minh-Quan Bui, Minh-Chau Nguyen, Tran-Binh Dang, Vu Tran, Le-Minh Nguyen, Ken Satoh

In this paper, we introduce our approaches using Transformer-based models for different problems of the COLIEE 2021 automatic legal text processing competition.

Pretrained Language Models

Sublanguage: A Serious Issue Affects Pretrained Models in Legal Domain

no code implementations15 Apr 2021 Ha-Thanh Nguyen, Le-Minh Nguyen

Legal English is a sublanguage that is important for everyone but not for everyone to understand.

SCNN: Swarm Characteristic Neural Network

no code implementations8 Mar 2021 Ha-Thanh Nguyen, Le-Minh Nguyen

Deep learning is a powerful approach with good performance on many different tasks.

Improving Multilingual Neural Machine Translation For Low-Resource Languages: French,English - Vietnamese

no code implementations16 Dec 2020 Thi-Vinh Ngo, Phuong-Thai Nguyen, Thanh-Le Ha, Khac-Quy Dinh, Le-Minh Nguyen

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.

Machine Translation Translation +1

Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation

no code implementations WS 2019 Thi-Vinh Ngo, Thanh-Le Ha, Phuong-Thai Nguyen, Le-Minh Nguyen

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 low-resource languages.

Machine Translation NMT +1

Dual Latent Variable Model for Low-Resource Natural Language Generation in Dialogue Systems

no code implementations CONLL 2018 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.

Text Generation Variational Inference

Adversarial Domain Adaptation for Variational Neural Language Generation in Dialogue Systems

no code implementations COLING 2018 Van-Khanh Tran, Le-Minh Nguyen

In this procedure, a model is first trained on a source domain data and then fine-tuned on a small set of target domain utterances under the guidance of two proposed critics.

Domain Adaptation Spoken Dialogue Systems +1

Combining Advanced Methods in Japanese-Vietnamese Neural Machine Translation

1 code implementation18 May 2018 Thi-Vinh Ngo, Thanh-Le Ha, Phuong-Thai Nguyen, Le-Minh Nguyen

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 data.

Machine Translation NMT +1

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