Fast Neural Ranking on Bipartite Graph Indices
Summary: Proposes BipartitE Graph INdices (BEGIN) to enable fast neural ranking by linking base items and sampled queries via neural scores. Extends graph-search techniques to non-convex, asymmetric neural measures; demonstrates effectiveness and efficiency. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shulong Tan
- 2. Weijie Zhao
- 3. Ping Li
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 |
| 11,079 | Complex-Path: Effective and Efficient Node Ranking with Paths in Billion-Scale Heterogeneous Graphs | 2024 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 34 | Similarity Search in High Dimensions via Hashing | 1999 | VLDB | 0.00076637636 |
| 212 | Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph | 2019 | VLDB | 0.00033913475 |
| 1,920 | Fast and Unified Local Search for Random Walk Based K-Nearest-Neighbor Query in Large Graphs | 2014 | SIGMOD | 0.00010090791 |
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