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.
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.
no code implementations • 12 Apr 2024 • Yizhi Pan, Junyi Xin, Tianhua Yang, Teeradaj Racharak, Le-Minh Nguyen, Guanqun Sun
Our approach, inspired by radiologists' working patterns, features two distinct modules: (i) \textbf{Mutual Inclusion of Position and Channel Attention (MIPC) module}: To enhance the precision of boundary segmentation in medical images, we introduce the MIPC module, which enhances the focus on channel information when extracting position features and vice versa; (ii) \textbf{GL-MIPC-Residue}: To improve the restoration of medical images, we propose the GL-MIPC-Residue, a global residual connection that enhances the integration of the encoder and decoder by filtering out invalid information and restoring the most effective information lost during the feature extraction process.
no code implementations • 6 Mar 2024 • Vu Tran, Ha-Thanh Nguyen, Trung Vo, Son T. Luu, Hoang-Anh Dang, Ngoc-Cam Le, Thi-Thuy Le, Minh-Tien Nguyen, Truong-Son Nguyen, Le-Minh Nguyen
In this new era of rapid AI development, especially in language processing, the demand for AI in the legal domain is increasingly critical.
no code implementations • 31 Jan 2024 • Chau Nguyen, Le-Minh Nguyen
ChatGPT, a large language model, is robust in many natural language processing tasks, including legal text entailment: when we set the temperature = 0 (the ChatGPT answers are deterministic) and prompt the model, it achieves 70. 64% accuracy on COLIEE 2022 dataset, which outperforms the previous SOTA of 67. 89%.
1 code implementation • 7 Jan 2024 • Chau Nguyen, Phuong Nguyen, Thanh Tran, Dat Nguyen, An Trieu, Tin Pham, Anh Dang, Le-Minh Nguyen
The Competition on Legal Information Extraction/Entailment (COLIEE) is held annually to encourage advancements in the automatic processing of legal texts.
1 code implementation • 19 Oct 2023 • Guanqun Sun, Yizhi Pan, Weikun Kong, Zichang Xu, Jianhua Ma, Teeradaj Racharak, Le-Minh Nguyen, Junyi Xin
Unlike earlier transformer-based U-net models, DA-TransUNet utilizes Transformers and DA-Block to integrate not only global and local features, but also image-specific positional and channel features, improving the performance of medical image segmentation.
no code implementations • 8 Jun 2023 • Thi-Hai-Yen Vuong, Ha-Thanh Nguyen, Quang-Huy Nguyen, Le-Minh Nguyen, Xuan-Hieu Phan
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 logical relationships.
no code implementations • 16 Dec 2022 • Ha-Thanh Nguyen, Vu Tran, Ngoc-Cam Le, Thi-Thuy Le, Quang-Huy Nguyen, Le-Minh Nguyen, Ken Satoh
First, legal reasoning can be performed on the basis of the binary tree representation of the regulations.
no code implementations • 13 Dec 2022 • Ha-Thanh Nguyen, Manh-Kien Phi, Xuan-Bach Ngo, Vu Tran, Le-Minh Nguyen, Minh-Phuong Tu
The performance of legal text retrieval depends, to a large extent, on the representation of text, both query and legal documents.
no code implementations • 13 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.
no code implementations • 11 Sep 2021 • Ha-Thanh Nguyen, Vu Tran, Tran-Binh Dang, Minh-Quan Bui, Minh-Phuong Nguyen, Le-Minh Nguyen
Attention is all we need as long as we have enough data.
no code implementations • 15 Apr 2021 • Ha-Thanh Nguyen, Le-Minh Nguyen
Legal English is a sublanguage that is important for everyone but not for everyone to understand.
no code implementations • 8 Mar 2021 • Ha-Thanh Nguyen, Le-Minh Nguyen
Deep learning is a powerful approach with good performance on many different tasks.
no code implementations • 16 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.
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.
1 code implementation • EMNLP (IWSLT) 2019 • Thi-Vinh Ngo, Thanh-Le Ha, Phuong-Thai Nguyen, Le-Minh Nguyen
While translating between East Asian languages, many works have discovered clear advantages of using characters as the translation unit.
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.
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.
1 code implementation • 18 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.
no code implementations • WS 2017 • Van-Khanh Tran, Le-Minh Nguyen
Natural language generation (NLG) is an important component in spoken dialogue systems.
no code implementations • CONLL 2017 • Van-Khanh Tran, Le-Minh Nguyen
Natural language generation (NLG) is a critical component in a spoken dialogue system.
no code implementations • 1 Jun 2017 • Van-Khanh Tran, Le-Minh Nguyen
Natural language generation (NLG) plays a critical role in spoken dialogue systems.