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When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction
Summary: EAGLE: lightweight T-GNN that fuses time-aware recent-neighbor aggregation with temporal personalized PageRank and adaptive weighting to trade off recency vs. global structure. Avoids multi-hop/message-memory overhead, giving superior accuracy and >50× speedups.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13970
- Venue
- VLDB
- Year
- 2025
- Pagerank
- 4.1905499e-05
- Overall Rank
- 10,681 | 25.77%
- DOI
-
10.14778/3748191.3748203
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No non-self incoming citations found for this paper in this database.
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 635 |
APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding |
2021 |
SIGMOD |
0.00018825777 |
| 1,388 |
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs |
2022 |
VLDB |
0.00012249747 |
| 3,715 |
Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank |
2023 |
VLDB |
6.8176818e-05 |
| 4,054 |
Orca: Scalable Temporal Graph Neural Network Training with Theoretical Guarantees |
2023 |
SIGMOD |
6.4910804e-05 |
| 4,209 |
Mining Bursting Core in Large Temporal Graphs |
2022 |
VLDB |
6.3511029e-05 |
| 4,484 |
Efficient Temporal Butterfly Counting and Enumeration on Temporal Bipartite Graphs |
2024 |
VLDB |
6.1426351e-05 |
| 4,889 |
GraphJet: Real-Time Content Recommendations at Twitter |
2016 |
VLDB |
5.8480413e-05 |
| 5,356 |
NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams |
2024 |
VLDB |
5.5514335e-05 |
| 5,452 |
Decoupled Graph Neural Networks for Large Dynamic Graphs |
2023 |
VLDB |
5.4972958e-05 |
| 5,485 |
ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs |
2024 |
VLDB |
5.4817019e-05 |
| 6,479 |
EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs |
2023 |
SIGMOD |
5.0405101e-05 |
| 7,014 |
SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement |
2024 |
SIGMOD |
4.8570865e-05 |
| 7,694 |
LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR |
2024 |
SIGMOD |
4.6712753e-05 |
| 7,714 |
Minimum Strongly Connected Subgraph Collection in Dynamic Graphs |
2024 |
VLDB |
4.6651585e-05 |
| 7,750 |
GENTI: GPU-powered Walk-based Subgraph Extraction for Scalable Representation Learning on Dynamic Graphs |
2024 |
VLDB |
4.6565447e-05 |
| 8,135 |
Towards Event Prediction in Temporal Graphs |
2022 |
VLDB |
4.5740737e-05 |
| 9,246 |
Efficient Algorithms for Pseudoarboricity Computation in Large Static and Dynamic Graphs |
2024 |
VLDB |
4.3648789e-05 |
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