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20132023
most citedWeakly-Supervised Scientific Document Classification via Retrieval-Augmented Multi-Stage Training

15 citations · 22 across the 4 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CL202315 cited

Weakly-Supervised Scientific Document Classification via Retrieval-Augmented Multi-Stage Training

Ran Xu, Yue Yu, Joyce C. Ho +1

Scientific document classification is a critical task for a wide range of applications, but the cost of obtaining massive amounts of human-labeled data can be prohibitive. To addre…

cs.AI2023

A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises

Hejie Cui, Jiaying Lu, Ran Xu +14

This comprehensive review aims to provide an overview of the current state of Healthcare Knowledge Graphs (HKGs), including their construction, utilization models, and applications…

cs.LG2023

PGB: A PubMed Graph Benchmark for Heterogeneous Network Representation Learning

Eric W Lee, Joyce C Ho

There has been rapid growth in biomedical literature, yet capturing the heterogeneity of the bibliographic information of these articles remains relatively understudied. Although g…

cs.LG2023

Neighborhood-Regularized Self-Training for Learning with Few Labels

Ran Xu, Yue Yu, Hejie Cui +5

Training deep neural networks (DNNs) with limited supervision has been a popular research topic as it can significantly alleviate the annotation burden. Self-training has been succ…

cs.LG202310 cited

MedDiff: Generating Electronic Health Records using Accelerated Denoising Diffusion Model

Huan He, Shifan Zhao, Yuanzhe Xi +1

Due to patient privacy protection concerns, machine learning research in healthcare has been undeniably slower and limited than in other application domains. High-quality, realisti…