When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction
Summary: EAGLE combines recent-neighbor aggregation with temporal personalized PageRank, adaptively weighting short-term preferences and long-range structural influence. Avoiding multi-hop propagation and memory-heavy state, it matches or exceeds T-GNN accuracy with over 50× speedups. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Haoyang LI (Hong Kong Polytechnic University)
- 2. Yuming XU (Hong Kong Polytechnic University; South China University of Technology)
- 3. Yiming LI (Hong Kong University of Science and Technology)
- 4. Hanmo LIU (Hong Kong University of Science and Technology)
- 5. Darian LI (Guangdong University of Technology; Hong Kong Polytechnic University)
- 6. Chen Jason ZHANG (Hong Kong Polytechnic University)
- 7. Lei CHEN (Foshan Youth Talent Research Institute; Hong Kong University of Science and Technology)
- 8. Qing LI (Hong Kong Polytechnic University)
BibTeX Citation
@article{li_vldb25,
title = {{When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction}},
author = {LI, Haoyang and XU, Yuming and LI, Yiming and LIU, Hanmo and LI, Darian and ZHANG, Chen Jason and CHEN, Lei and LI, Qing},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {10},
pages = {3396--3405},
doi = {10.14778/3748191.3748203},
url = {https://doi.org/10.14778/3748191.3748203},
year = {2025}
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