MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest
Summary: Breaks Pinterest’s heterogeneous entity interactions into multiple disjoint bipartite graphs and introduces MultiBiSage, a data-efficient GCN that fuses embeddings from these bipartite graphs while requiring minimal changes to existing PinSage infrastructure. Trained on six bipartite graphs at web scale, MultiBiSage significantly outperforms deployed PinSage on engagement metrics and generalizes to public datasets. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Saket Gurukar
- 2. Nikil Pancha
- 3. Andrew Zhai
- 4. Eric Kim
- 5. Samson Hu
- 6. Srinivasan Parthasarathy
- 7. Charles Rosenberg
- 8. Jure Leskovec
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,233 | RoarGraph: A Projected Bipartite Graph for Efficient Cross-Modal Approximate Nearest Neighbor Search | 2024 | VLDB | 5.6131833e-05 |
| 8,737 | Scheduling Data Processing Pipelines for Incremental Training on MLP-based Recommendation Models | 2025 | SIGMOD | 4.456315e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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