most citedBianCang: A Traditional Chinese Medicine Large Language Model

29 citations · 45 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2024★ 29 cited

BianCang: A Traditional Chinese Medicine Large Language Model

Sibo Wei, Xueping Peng, Yi-Fei Wang +8

The surge of large language models (LLMs) has driven significant progress in medical applications, including traditional Chinese medicine (TCM). However, current medical LLMs strug…

cs.CL2020★ 3 cited

Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention

Yang Li, Tao Shen, Guodong Long +3

Wrong labeling problem and long-tail relations are two main challenges caused by distant supervision in relation extraction. Recent works alleviate the wrong labeling by selective…

cs.CL2020

RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion

Hao Huang, Guodong Long, Tao Shen +2

Many graph embedding approaches have been proposed for knowledge graph completion via link prediction. Among those, translating embedding approaches enjoy the advantages of light-w…

cs.LG2020

BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes

Xueping Peng, Guodong Long, Tao Shen +3

Electronic health records (EHRs) are longitudinal records of a patient's interactions with healthcare systems. A patient's EHR data is organized as a three-level hierarchy from top…

cs.LG2020★ 5 cited

Self-Attention Enhanced Patient Journey Understanding in Healthcare System

Xueping Peng, Guodong Long, Tao Shen +2

Understanding patients' journeys in healthcare system is a fundamental prepositive task for a broad range of AI-based healthcare applications. This task aims to learn an informativ…

cs.CL2020★ 8 cited

Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning

Tao Shen, Yi Mao, Pengcheng He +3

In this work, we aim at equipping pre-trained language models with structured knowledge. We present two self-supervised tasks learning over raw text with the guidance from knowledg…