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Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank

Summary: Links T-GNN temporal message passing to temporal random walks and proposes T-PPR, a parameterized influence score showing a few temporal neighbors suffice for accurate representations. Introduces Zebra: a scalable framework with a single-scan top-k T-PPR algorithm (provable approximation) that aggregates top influencers, delivering up to 100× speedups and often better accuracy. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
hb4020a498a920ce3
Venue
VLDB
Year
2023
Pagerank
7.7471344e-05
Overall Rank
3,017 | 79.72%
DOI
10.14778/3583140.3583150

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{li_vldb23,
        title = {{Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank}},
        author = {Li, Yiming and Shen, Yanyan and Chen, Lei and Yuan, Mingxuan},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {6},
        pages = {1332--1345},
        doi = {10.14778/3583140.3583150},
        url = {https://doi.org/10.14778/3583140.3583150},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 20 of 20 citing papers.

Rank Citing Paper Year Venue Pagerank
4,502 NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams 2024 VLDB 6.5740722e-05
4,764 ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs 2024 VLDB 6.4276208e-05
4,825 DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning 2024 VLDB 6.3923554e-05
5,310 DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training 2024 VLDB 6.1857447e-05
6,109 GENTI: GPU-powered Walk-based Subgraph Extraction for Scalable Representation Learning on Dynamic Graphs 2024 VLDB 5.8845577e-05
6,166 Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving 2025 SIGMOD 5.8631131e-05
6,669 Efficient Training of Graph Neural Networks on Large Graphs 2024 VLDB 5.7147311e-05
6,826 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD 5.6700316e-05
8,670 Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense 2024 VLDB 5.2917782e-05
8,671 Enabling Window-Based Monotonic Graph Analytics with Reusable Transitional Results for Pattern-Consistent Queries 2024 VLDB 5.2917782e-05
9,232 PipeTGL: (Near) Zero Bubble Memory-based Temporal Graph Neural Network Training via Pipeline Optimization 2025 VLDB 5.2056825e-05
9,234 Effective and Efficient Distributed Temporal Graph Learning through Hotspot Memory Sharing 2025 VLDB 5.2056825e-05
9,528 Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs 2023 VLDB 5.1656406e-05
10,263 BIRD: Efficient Approximation of Bidirectional Hidden Personalized PageRank 2024 VLDB 5.050482e-05
10,535 SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine 2026 SIGMOD 4.9793485e-05
10,779 PRISM: A Training System to Unlock the Potential of Temporal Graph Learning Through Staleness Avoidance 2026 VLDB 4.9793485e-05
11,066 Understanding Evolving Graph Structures for Large Discrete-Time Dynamic Graph Representation 2026 VLDB 4.9793485e-05
11,314 When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction 2025 VLDB 4.9793485e-05
11,458 Efficient Graph Embedding Generation and Update for Large-Scale Temporal Graph 2025 VLDB 4.9793485e-05
11,459 Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours 2025 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
556 Fast Incremental and Personalized PageRank 2011 VLDB 0.00016500392
881 APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding 2021 SIGMOD 0.00013278822
1,364 TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs 2022 VLDB 0.00010914152
1,419 Fast and Exact Top-k Search for Random Walk with Restart 2012 VLDB 0.00010728945
1,604 Fast and Unified Local Search for Random Walk Based K-Nearest-Neighbor Query in Large Graphs 2014 SIGMOD 0.00010095949
1,860 Efficient Ad-hoc Search for Personalized PageRank 2013 SIGMOD 9.4876834e-05
2,183 Unifying the Global and Local Approaches: An Efficient Power Iteration with Forward Push 2021 SIGMOD 8.8962182e-05
2,258 HubPPR: Effective Indexing for Approximate Personalized PageRank 2017 VLDB 8.7385422e-05
3,653 Realtime Top-k Personalized PageRank over Large Graphs on GPUs 2020 VLDB 7.1288161e-05
3,899 Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization 2021 VLDB 6.9358695e-05
4,101 TopPPR: Top-k Personalized PageRank Queries with Precision Guarantees on Large Graphs 2018 SIGMOD 6.8073016e-05
5,236 Edge-based Local Push for Personalized PageRank 2022 VLDB 6.2171816e-05
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Semantically Similar Papers

# Overall Rank Paper Year Venue
1 3,653 Realtime Top-k Personalized PageRank over Large Graphs on GPUs 2020 VLDB
2 4,101 TopPPR: Top-k Personalized PageRank Queries with Precision Guarantees on Large Graphs 2018 SIGMOD
3 5,300 Parallel Personalized PageRank on Dynamic Graphs 2018 VLDB
4 4,264 Personalized PageRank on Evolving Graphs with an Incremental Index-Update Scheme 2023 SIGMOD
5 6,826 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD
6 1,835 Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank 2020 VLDB
7 9,528 Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs 2023 VLDB
8 1,364 TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs 2022 VLDB
9 11,459 Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours 2025 VLDB
10 11,314 When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction 2025 VLDB