382 citations · 495 across the 11 of their papers we have counts for
12 papers
Exploring Large Language Models for Knowledge Graph Completion
Liang Yao, Jiazhen Peng, Chengsheng Mao +1
Knowledge graphs play a vital role in numerous artificial intelligence tasks, yet they frequently face the issue of incompleteness. In this study, we explore utilizing Large Langua…
Friend Ranking in Online Games via Pre-training Edge Transformers
Liang Yao, Jiazhen Peng, Shenggong Ji +4
Friend recall is an important way to improve Daily Active Users (DAU) in online games. The problem is to generate a proper lost friend ranking list essentially. Traditional friend…
Towards Expressive Graph Representation
Chengsheng Mao, Liang Yao, Yuan Luo
Graph Neural Network (GNN) aggregates the neighborhood of each node into the node embedding and shows its powerful capability for graph representation learning. However, most exist…
KG-BERT: BERT for Knowledge Graph Completion
Liang Yao, Chengsheng Mao, Yuan Luo
Knowledge graphs are important resources for many artificial intelligence tasks but often suffer from incompleteness. In this work, we propose to use pre-trained language models fo…
Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study
Prakash Adekkanattu, Guoqian Jiang, Yuan Luo +14
While natural language processing (NLP) of unstructured clinical narratives holds the potential for patient care and clinical research, portability of NLP approaches across multipl…
ImageGCN: Multi-Relational Image Graph Convolutional Networks for Disease Identification with Chest X-rays
Chengsheng Mao, Liang Yao, Yuan Luo
Image representation is a fundamental task in computer vision. However, most of the existing approaches for image representation ignore the relations between images and consider ea…
Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes
Yikuan Li, Liang Yao, Chengsheng Mao +3
Acute kidney injury (AKI) in critically ill patients is associated with significant morbidity and mortality. Development of novel methods to identify patients with AKI earlier will…
Distribution Networks for Open Set Learning
Chengsheng Mao, Liang Yao, Yuan Luo
In open set learning, a model must be able to generalize to novel classes when it encounters a sample that does not belong to any of the classes it has seen before. Open set learni…
Deep Generative Classifiers for Thoracic Disease Diagnosis with Chest X-ray Images
Chengsheng Mao, Yiheng Pan, Zexian Zeng +2
Thoracic diseases are very serious health problems that plague a large number of people. Chest X-ray is currently one of the most popular methods to diagnose thoracic diseases, pla…
Graph Convolutional Networks for Text Classification
Liang Yao, Chengsheng Mao, Yuan Luo
Text classification is an important and classical problem in natural language processing. There have been a number of studies that applied convolutional neural networks (convolutio…
Clinical Text Classification with Rule-based Features and Knowledge-guided Convolutional Neural Networks
Liang Yao, Chengsheng Mao, Yuan Luo
Clinical text classification is an important problem in medical natural language processing. Existing studies have conventionally focused on rules or knowledge sources-based featur…
Developing a Portable Natural Language Processing Based Phenotyping System
Himanshu Sharma, Chengsheng Mao, Yizhen Zhang +7
This paper presents a portable phenotyping system that is capable of integrating both rule-based and statistical machine learning based approaches. Our system utilizes UMLS to extr…