83 citations · 292 across the 25 of their papers we have counts for
25 papers
Motif-aware Attribute Masking for Molecular Graph Pre-training
Eric Inae, Gang Liu, Meng Jiang
Attribute reconstruction is used to predict node or edge features in the pre-training of graph neural networks. Given a large number of molecules, they learn to capture structural…
Embedding Mental Health Discourse for Community Recommendation
Hy Dang, Bang Nguyen, Noah Ziems +1
Our paper investigates the use of discourse embedding techniques to develop a community recommendation system that focuses on mental health support groups on social media. Social m…
A Quantitative Review on Language Model Efficiency Research
Meng Jiang, Hy Dang, Lingbo Tong
Language models (LMs) are being scaled and becoming powerful. Improving their efficiency is one of the core research topics in neural information processing systems. Tay et al. (20…
Semi-Supervised Graph Imbalanced Regression
Gang Liu, Tong Zhao, Eric Inae +2
Data imbalance is easily found in annotated data when the observations of certain continuous label values are difficult to collect for regression tasks. When they come to molecule…
Data-Centric Learning from Unlabeled Graphs with Diffusion Model
Gang Liu, Eric Inae, Tong Zhao +3
Graph property prediction tasks are important and numerous. While each task offers a small size of labeled examples, unlabeled graphs have been collected from various sources and a…
Very Large Language Model as a Unified Methodology of Text Mining
Meng Jiang
Text data mining is the process of deriving essential information from language text. Typical text mining tasks include text categorization, text clustering, topic modeling, inform…