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GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking., , and . CoRR, (2023)Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach., , , , , and . CoRR, (2022)Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective., , , , , and . CoRR, (2021)MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution., , , , , and . WSDM, page 132-140. ACM, (2023)Revisiting Code Search in a Two-Stage Paradigm., , , , , , and . WSDM, page 994-1002. ACM, (2023)Source Free Graph Unsupervised Domain Adaptation., , , , , , , and . WSDM, page 520-528. ACM, (2024)Tag2Vec: Learning Tag Representations in Tag Networks., , , , , and . WWW, page 3314-3320. ACM, (2019)Concept Understanding in Large Language Models: An Empirical Study., , and . Tiny Papers @ ICLR, OpenReview.net, (2023)Network Embedding on Hierarchical Community Structure Network., , , , and . ACM Trans. Knowl. Discov. Data, 15 (4): 62:1-62:23 (2021)TAROT: A Hierarchical Framework with Multitask co-pretraining on Semi-Structured Data Towards Effective Person-Job fit., , , , , , , , , and . ICASSP, page 12046-12050. IEEE, (2024)