1 code implementation • 21 Feb 2024 • Jiahao Zhang, Rui Xue, Wenqi Fan, Xin Xu, Qing Li, Jian Pei, Xiaorui Liu
In this paper, we propose a Linear-Time Graph Neural Network (LTGNN) to scale up GNN-based recommender systems to achieve comparable scalability as classic MF approaches while maintaining GNNs' powerful expressiveness for superior prediction accuracy.
no code implementations • 7 Dec 2023 • Rui Xue, Xipeng Shen, Ruozhou Yu, Xiaorui Liu
In this work, we introduce a novel and efficient approach for the end-to-end fine-tuning of Large Language Models (LLMs) on TAGs, named LEADING.
1 code implementation • 3 Feb 2023 • Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu
Recent works have demonstrated the benefits of capturing long-distance dependency in graphs by deeper graph neural networks (GNNs).
no code implementations • 19 May 2020 • Can Tan, Rui Xue, Lei-Ming Du, Shao-Qiang Xi, Ze-Rui Wang, Zhao-Hua Xie
(4) There is an anti-correlation between the peak energy of SEDs ($\gamma_{\rm peak}$) and the jet power ($P_{\rm jet}$), which is consistent with the blazar sequence.
High Energy Astrophysical Phenomena
no code implementations • 29 Feb 2020 • Ren Kong, Guangbo Yang, Rui Xue, Ming Liu, Feng Wang, Jianping Hu, Xiaoqiang Guo, Shan Chang
Motivation: The coronavirus disease 2019 (COVID-19) caused by a new type of coronavirus has been emerging from China and led to thousands of death globally since December 2019.