activity
20172021
most citedNNVLP: A Neural Network-Based Vietnamese Language Processing Toolkit

5 citations · 9 across the 6 of their papers we have counts for

collaborators

9 papers

cs.LG2021

Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning

Thai-Hoang Pham, Changchang Yin, Laxmi Mehta +2

Complication risk profiling is a key challenge in the healthcare domain due to the complex interaction between heterogeneous entities (e.g., visit, disease, medication) in clinical…

cs.CL20211 cited

TransICD: Transformer Based Code-wise Attention Model for Explainable ICD Coding

Biplob Biswas, Thai-Hoang Pham, Ping Zhang

International Classification of Disease (ICD) coding procedure which refers to tagging medical notes with diagnosis codes has been shown to be effective and crucial to the billing…

cs.CL20193 cited

Multi-Task Learning with Contextualized Word Representations for Extented Named Entity Recognition

Thai-Hoang Pham, Khai Mai, Nguyen Minh Trung +4

Fine-Grained Named Entity Recognition (FG-NER) is critical for many NLP applications. While classical named entity recognition (NER) has attracted a substantial amount of research,…

cs.CL2017

Vietnamese Semantic Role Labelling

Phuong Le-Hong, Thai Hoang Pham, Xuan Khoai Pham +3

In this paper, we study semantic role labelling (SRL), a subtask of semantic parsing of natural language sentences and its application for the Vietnamese language. We present our e…

cs.CL2017

On the Use of Machine Translation-Based Approaches for Vietnamese Diacritic Restoration

Thai-Hoang Pham, Xuan-Khoai Pham, Phuong Le-Hong

This paper presents an empirical study of two machine translation-based approaches for Vietnamese diacritic restoration problem, including phrase-based and neural-based machine tra…

cs.CL2017

An Empirical Study of Discriminative Sequence Labeling Models for Vietnamese Text Processing

Phuong Le-Hong, Minh Pham Quang Nhat, Thai-Hoang Pham +2

This paper presents an empirical study of two widely-used sequence prediction models, Conditional Random Fields (CRFs) and Long Short-Term Memory Networks (LSTMs), on two fundament…