no code implementations • 13 Dec 2023 • Nhu-Thanh Nguyen, Khoa Thi-Kim Phan, Duc-Vu Nguyen, Ngan Luu-Thuy Nguyen
Abuse in its various forms, including physical, psychological, verbal, sexual, financial, and cultural, has a negative impact on mental health.
no code implementations • 18 Oct 2023 • Duc-Vu Nguyen, Quoc-Nam Nguyen
Our evaluation of six well-known LLMs, namely BLOOMZ-7. 1B-MT, LLaMA-2-7B, LLaMA-2-70B, GPT-3, GPT-3. 5, and GPT-4. 0, on the ViMMRC 1. 0 and ViMMRC 2. 0 benchmarks and our proposed dataset shows promising results on the MCSB ability of LLMs for Vietnamese.
1 code implementation • 17 Oct 2023 • Quoc-Nam Nguyen, Thang Chau Phan, Duc-Vu Nguyen, Kiet Van Nguyen
English and Chinese, known as resource-rich languages, have witnessed the strong development of transformer-based language models for natural language processing tasks.
Vietnamese Language Models Vietnamese Social Media Text Processing +1
no code implementations • 9 Sep 2023 • Vu-Thuan Doan, Quoc-Truong Truong, Duc-Vu Nguyen, Vinh-Tiep Nguyen, Thuy-Ngan Nguyen Luu
Furthermore, the availability of pretrained LLMs and instruction-tune datasets for Vietnamese language is limited.
no code implementations • 1 Jan 2023 • Hang Thi-Thu Le, Viet-Duc Ho, Duc-Vu Nguyen, Ngan Luu-Thuy Nguyen
The classification of answerability questions is a relatively significant sub-task in machine reading comprehension; however, there haven't been many studies.
Machine Reading Comprehension Vietnamese Machine Reading Comprehension +1
no code implementations • 1 Jan 2023 • Duc-Vu Nguyen, Ngan Luu-Thuy Nguyen
To the best of our knowledge, this paper made the first attempt to answer whether word segmentation is necessary for Vietnamese sentiment classification.
no code implementations • 1 Jan 2023 • Quoc-Loc Duong, Duc-Vu Nguyen, Ngan Luu-Thuy Nguyen
The experimental results give conclusions about the influence and role of semantic representation on Vietnamese in understanding natural language.
Natural Language Inference Natural Language Understanding +2
no code implementations • PACLIC 2021 • Duc-Vu Nguyen, Linh-Bao Vo, Ngoc-Linh Tran, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
Previous studies on joint Chinese word segmentation and part-of-speech tagging mainly follow the character-based tagging model focusing on modeling n-gram features.
1 code implementation • 15 Oct 2021 • Kim Thi-Thanh Nguyen, Sieu Khai Huynh, Luong Luc Phan, Phuc Huynh Pham, Duc-Vu Nguyen, Kiet Van Nguyen
Aspect-based sentiment analysis plays an essential role in natural language processing and artificial intelligence.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +4
no code implementations • 1 Oct 2021 • Duc-Vu Nguyen, Linh-Bao Vo, Dang Van Thin, Ngan Luu-Thuy Nguyen
In this paper, we propose a span labeling approach to model n-gram information for Vietnamese word segmentation, namely SPAN SEG.
1 code implementation • 24 Feb 2021 • Duc-Vu Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
In this paper, we implement this idea to improve word segmentation and part of speech tagging the Vietnamese language by employing a simplified constituency parser.
no code implementations • 19 Oct 2020 • Tuan-Vi Tran, Xuan-Thien Pham, Duc-Vu Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
In this work, we use a span-based approach for Vietnamese constituency parsing.
no code implementations • 30 Sep 2020 • Kiet Van Nguyen, Duc-Vu Nguyen, Anh Gia-Tuan Nguyen, Ngan Luu-Thuy Nguyen
Due to the lack of benchmark datasets for Vietnamese, we present the Vietnamese Question Answering Dataset (UIT-ViQuAD), a new dataset for the low-resource language as Vietnamese to evaluate MRC models.
no code implementations • 19 Jun 2020 • Kiet Van Nguyen, Tin Van Huynh, Duc-Vu Nguyen, Anh Gia-Tuan Nguyen, Ngan Luu-Thuy Nguyen
In particular, we develop a process of creating a corpus for the Vietnamese machine reading comprehension.
1 code implementation • 14 Jun 2020 • Duc-Vu Nguyen, Dang Van Thin, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
In this paper, we approach Vietnamese word segmentation as a binary classification by using the Support Vector Machine classifier.
no code implementations • 21 Nov 2019 • Vong Anh Ho, Duong Huynh-Cong Nguyen, Danh Hoang Nguyen, Linh Thi-Van Pham, Duc-Vu Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
In this task, the result is not produced in terms of either polarity: positive or negative or in the form of rating (from 1 to 5) but of a more detailed level of analysis in which the results are depicted in more expressions like sadness, enjoyment, anger, disgust, fear, and surprise.
no code implementations • SEMEVAL 2019 • Duc-Vu Nguyen, Thin Dang, Ngan Nguyen
This paper describes the system of NLP@UIT that participated in Task 4 of SemEval-2019.