DBScholar

Back to papers

EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs

Summary: EARLY proposes an efficient and reliable GNN update mechanism for dynamic graphs. It identifies top-k influential nodes affected by events and applies diversity-aware, layer-wise sampling to curb neighbor redundancy, reducing sampling error and yielding more reliable representations under continuous updates. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6728
Venue
SIGMOD
Year
2023
Pagerank
5.9366952e-05
Overall Rank
6,261 | 57.05%
DOI
10.1145/3589308

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{li_sigmod23,
        title = {{EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs}},
        author = {Li, Haoyang and Chen, Lei},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3589308},
        url = {https://dl.acm.org/doi/10.1145/3589308},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Rank Citing Paper Year Venue Pagerank
5,760 DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training 2024 VLDB 6.0961929e-05
6,900 Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving 2025 SIGMOD 5.7430032e-05
8,503 Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense 2024 VLDB 5.4132367e-05
10,330 SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine 2026 SIGMOD 5.093636e-05
10,521 Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling 2026 VLDB 5.093636e-05
10,620 Understanding Evolving Graph Structures for Large Discrete-Time Dynamic Graph Representation 2026 VLDB 5.093636e-05
10,780 SWASH: A Flexible Communication Framework with Sliding Window-Based Cache Sharing for Scalable DGNN Training 2025 SIGMOD 5.093636e-05
10,922 When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction 2025 VLDB 5.093636e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 18 of 18 cited papers.

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

Rank Cited Paper Year Venue Pagerank
223 AliGraph: A Comprehensive Graph Neural Network Platform 2019 VLDB 0.00024182473
556 Fast Incremental and Personalized PageRank 2011 VLDB 0.00016564032
920 APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding 2021 SIGMOD 0.00013209734
945 Fast Personalized PageRank on MapReduce 2011 SIGMOD 0.00013066956
1,409 TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs 2022 VLDB 0.00010854808
1,968 Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank 2020 VLDB 9.3752727e-05
2,209 Regular Path Query Evaluation on Streaming Graphs 2020 SIGMOD 8.9437338e-05
2,383 ICS-GNN: Lightweight Interactive Community Search via Graph Neural Network 2021 VLDB 8.6527736e-05
2,695 NeutronStar: Distributed GNN Training with Hybrid Dependency Management 2022 SIGMOD 8.2468134e-05
2,873 Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed 2022 VLDB 8.0099557e-05
3,221 Camel: Managing Data for Efficient Stream Learning 2022 SIGMOD 7.6271601e-05
3,850 Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization 2021 VLDB 7.0742748e-05
4,905 Medical Entity Disambiguation Using Graph Neural Networks 2021 SIGMOD 6.4497268e-05
5,118 Efficient Streaming Subgraph Isomorphism with Graph Neural Networks 2021 VLDB 6.3580186e-05
5,432 Scalable and Effective Bipartite Network Embedding 2022 SIGMOD 6.2211042e-05
6,146 METRO: A Generic Graph Neural Network Framework for Multivariate Time Series Forecasting 2022 VLDB 5.9601852e-05
6,550 Reliable Data Distillation on Graph Convolutional Network 2020 SIGMOD 5.8430465e-05
9,504 Points-of-Interest Relationship Inference with Spatial-enriched Graph Neural Networks 2022 VLDB 5.2585442e-05
Previous Page 1 / 1 Next

Semantically Similar Papers

# Overall Rank Paper Year Venue
1 1,863 ByteGNN: Efficient Graph Neural Network Training at Large Scale 2022 VLDB
2 8,454 D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks 2024 VLDB
3 8,912 Historical Embedding-Guided Efficient Large-Scale Federated Graph Learning 2024 SIGMOD
4 2,640 Scalable and Efficient Full-Graph GNN Training for Large Graphs 2023 SIGMOD
5 11,110 Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours 2025 VLDB
6 7,374 ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling 2023 SIGMOD
7 6,730 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD
8 10,975 Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation 2025 VLDB
9 6,630 Efficient Training of Graph Neural Networks on Large Graphs 2024 VLDB
10 4,980 Decoupled Graph Neural Networks for Large Dynamic Graphs 2023 VLDB