52 citations · 215 across the 28 of their papers we have counts for
14 papers · 1 filter
When Giant Language Brains Just Aren't Enough! Domain Pizzazz with Knowledge Sparkle Dust
Minh-Tien Nguyen, Duy-Hung Nguyen, Shahab Sabahi +3
Large language models (LLMs) have significantly advanced the field of natural language processing, with GPT models at the forefront. While their remarkable performance spans a rang…
CinPatent: Datasets for Patent Classification
Minh-Tien Nguyen, Nhung Bui, Manh Tran-Tien +2
Patent classification is the task that assigns each input patent into several codes (classes). Due to its high demand, several datasets and methods have been introduced. However, t…
Meeting Decision Tracker: Making Meeting Minutes with De-Contextualized Utterances
Shumpei Inoue, Hy Nguyen, Pham Viet Hoang +2
Meetings are a universal process to make decisions in business and project collaboration. The capability to automatically itemize the decisions in daily meetings allows for extensi…
MTet: Multi-domain Translation for English and Vietnamese
Chinh Ngo, Trieu H. Trinh, Long Phan +5
We introduce MTet, the largest publicly available parallel corpus for English-Vietnamese translation. MTet consists of 4.2M high-quality training sentence pairs and a multi-domain…
Jointly Learning Span Extraction and Sequence Labeling for Information Extraction from Business Documents
Nguyen Hong Son, Hieu M. Vu, Tuan-Anh D. Nguyen +1
This paper introduces a new information extraction model for business documents. Different from prior studies which only base on span extraction or sequence labeling, the model tak…
Enhance Incomplete Utterance Restoration by Joint Learning Token Extraction and Text Generation
Shumpei Inoue, Tsungwei Liu, Nguyen Hong Son +1
This paper introduces a model for incomplete utterance restoration (IUR) called JET (\textbf{J}oint learning token \textbf{E}xtraction and \textbf{T}ext generation). Different from…
Robust Deep Reinforcement Learning for Extractive Legal Summarization
Duy-Hung Nguyen, Bao-Sinh Nguyen, Nguyen Viet Dung Nghiem +4
Automatic summarization of legal texts is an important and still a challenging task since legal documents are often long and complicated with unusual structures and styles. Recent…
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…
ParaLaw Nets -- Cross-lingual Sentence-level Pretraining for Legal Text Processing
Ha-Thanh Nguyen, Vu Tran, Phuong Minh Nguyen +6
Ambiguity is a characteristic of natural language, which makes expression ideas flexible. However, in a domain that requires accurate statements, it becomes a barrier. Specifically…
JNLP Team: Deep Learning Approaches for Legal Processing Tasks in COLIEE 2021
Ha-Thanh Nguyen, Phuong Minh Nguyen, Thi-Hai-Yen Vuong +6
COLIEE is an annual competition in automatic computerized legal text processing. Automatic legal document processing is an ambitious goal, and the structure and semantics of the la…
Gunrock 2.0: A User Adaptive Social Conversational System
Kaihui Liang, Austin Chau, Yu Li +8
Gunrock 2.0 is built on top of Gunrock with an emphasis on user adaptation. Gunrock 2.0 combines various neural natural language understanding modules, including named entity detec…
JNLP Team: Deep Learning for Legal Processing in COLIEE 2020
Ha-Thanh Nguyen, Hai-Yen Thi Vuong, Phuong Minh Nguyen +7
We propose deep learning based methods for automatic systems of legal retrieval and legal question-answering in COLIEE 2020. These systems are all characterized by being pre-traine…
Building Legal Case Retrieval Systems with Lexical Matching and Summarization using A Pre-Trained Phrase Scoring Model
Vu Tran, Minh Le Nguyen, Ken Satoh
We present our method for tackling the legal case retrieval task of the Competition on Legal Information Extraction/Entailment 2019. Our approach is based on the idea that summariz…
Automatic Catchphrase Extraction from Legal Case Documents via Scoring using Deep Neural Networks
Vu Tran, Minh Le Nguyen, Ken Satoh
In this paper, we present a method of automatic catchphrase extracting from legal case documents. We utilize deep neural networks for constructing scoring model of our extraction s…