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Found 5 papers, 2 papers with code
Linear-Time Graph Neural Networks for Scalable Recommendations
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.
Efficient Large Language Models Fine-Tuning On Graphs
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.
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
Recent works have demonstrated the benefits of capturing long-distance dependency in graphs by deeper graph neural networks (GNNs).
The physical properties of $Fermi$-4LAC flat spectrum radio quasars
(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
COVID-19 Docking Server: A meta server for docking small molecules, peptides and antibodies against potential targets of COVID-19
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.
