Papers › PyTorch-BigGraph: A Large-scale Graph Embedding System
PyTorch-BigGraph: A Large-scale Graph Embedding System
Adam Lerer, Ledell Wu, Jiajun Shen, Timothee Lacroix, Luca Wehrstedt, Abhijit Bose, Alex Peysakhovich
Graph embedding methods produce unsupervised node features from graphs that can then be used for a variety of machine learning tasks. Modern graphs, particularly in industrial applications, contain billions of nodes and trillions of edges, which exceeds the capability of existing embedding systems. We present PyTorch-BigGraph (PBG), an embedding system that incorporates several modifications to traditional multi-relation embedding systems that allow it to scale to graphs with billions of nodes and trillions of edges. PBG uses graph partitioning to train arbitrarily large embeddings on either a single machine or in a distributed environment. We demonstrate comparable performance with existing embedding systems on common benchmarks, while allowing for scaling to arbitrarily large graphs and parallelization on multiple machines. We train and evaluate embeddings on several large social network graphs as well as the full Freebase dataset, which contains over 100 million nodes and 2 billion edges.
In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Link Prediction | FB15k | PyTorch BigGraph (ComplEx) | Hits@10 | 0.872 | #5 of 10 | Archive leaderboard | report |
| Link Prediction | FB15k | PyTorch BigGraph (ComplEx) | MRR | 0.79 | #5 of 10 | Archive leaderboard | report |
| Link Prediction | FB15k | PyTorch BigGraph (ComplEx) | MRR raw | 0.242 | #5 of 10 | Archive leaderboard | report |
| Link Prediction | LiveJournal | PBG (1 partition) | Hits@10 | 0.857 | #1 of 2 | Archive leaderboard | report |
| Link Prediction | LiveJournal | PBG (1 partition) | MR | 245.9 | #1 of 2 | Archive leaderboard | report |
| Link Prediction | LiveJournal | PyTorch BigGraph | MRR | 0.749 | #2 of 2 | Archive leaderboard | report |
| Link Prediction | YouTube | PyTorch BigGraph | Macro F1 | 40.9 | #2 of 2 | Archive leaderboard | report |
| Link Prediction | YouTube | PyTorch BigGraph | Micro F1 | 48 | #2 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections