8 citations · 18 across the 26 of their papers we have counts for
5 papers · 1 filter
Transforming the Hybrid Cloud for Emerging AI Workloads
Deming Chen, Alaa Youssef, Ruchi Pendse +42
This white paper, developed through close collaboration between IBM Research and UIUC researchers within the IIDAI Institute, envisions transforming hybrid cloud systems to meet th…
What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs
Dongqi Fu, Liri Fang, Zihao Li +3
Graphs, as a relational data structure, have been widely used for various application scenarios, like molecule design and recommender systems. Recently, large language models (LLMs…
Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
Wenxuan Bao, Zhichen Zeng, Zhining Liu +2
Powerful as they are, graph neural networks (GNNs) are known to be vulnerable to distribution shifts. Recently, test-time adaptation (TTA) has attracted attention due to its abilit…
Generating Fine-Grained Causality in Climate Time Series Data for Forecasting and Anomaly Detection
Dongqi Fu, Yada Zhu, Hanghang Tong +3
Understanding the causal interaction of time series variables can contribute to time series data analysis for many real-world applications, such as climate forecasting and extreme…
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections
Dongqi Fu, Zhigang Hua, Yan Xie +7
Graph transformer has been proven as an effective graph learning method for its adoption of attention mechanism that is capable of capturing expressive representations from complex…