Decoupled Graph Neural Networks for Large Dynamic Graphs

Summary: Decoupled GNN with a unified dynamic propagation primitive that handles both continuous- and discrete-time graph streams, confining expensive structure computations to propagation. Downstream sequence models are plug-and-play, enabling SOTA accuracy and extreme scalability (tested on >1B edges, >100M nodes). (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13074
Venue: VLDB
Year: 2023
Pagerank: 5.5025808e-05
Overall Rank: 5,443 | 62.14%
DOI: 10.14778/3598581.3598595

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
7,749	GENTI: GPU-powered Walk-based Subgraph Extraction for Scalable Representation Learning on Dynamic Graphs	2024	VLDB	4.6610143e-05
8,510	Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense	2024	VLDB	4.4952414e-05
9,395	NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism	2025	VLDB	4.3441378e-05
9,484	Enabling Window-Based Monotonic Graph Analytics with Reusable Transitional Results for Pattern-Consistent Queries	2024	VLDB	4.3341665e-05
10,233	Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling	2026	VLDB	4.1945683e-05
10,322	Understanding Evolving Graph Structures for Large Discrete-Time Dynamic Graph Representation	2026	VLDB	4.1945683e-05
10,570	NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism	2025	VLDB	4.1945683e-05
10,673	When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction	2025	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
636	APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding	2021	SIGMOD	0.00018846494
1,387	TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs	2022	VLDB	0.00012261568

Semantically Similar Papers

Overall Rank	Paper	Year	Venue	Pagerank
5,018	DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks	2023	SIGMOD	5.7567672e-05
4,577	Accelerating Dynamic Graph Analytics on GPUs	2018	VLDB	6.0709631e-05
1,387	TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs	2022	VLDB	0.00012261568
10,322	Understanding Evolving Graph Structures for Large Discrete-Time Dynamic Graph Representation	2026	VLDB	4.1945683e-05
3,087	Scalable and Efficient Full-Graph GNN Training for Large Graphs	2023	SIGMOD	7.5939896e-05
7,014	SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement	2024	SIGMOD	4.8616315e-05
8,463	D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks	2024	VLDB	4.5052127e-05
10,887	Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours	2025	VLDB	4.1945683e-05
6,942	Efficient Training of Graph Neural Networks on Large Graphs	2024	VLDB	4.8922884e-05
6,485	EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs	2023	SIGMOD	5.0453531e-05