Back to papers
Reveal Hidden Pitfalls and Navigate Next Generation of Vector Similarity Search from Task-Centric Views: [Experiments & Analysis]
Summary: Iceberg: task-centric benchmark for VSS beyond recall/latency on metric ground truth; evaluates end-to-end pipeline across 8 datasets, exposing an Information Loss Funnel (embedding loss, metric misuse, distribution sensitivity). Re-ranks 13 VSS methods and provides interpretable guidance for workload-specific method selection.
(summarized by gpt-5-mini on Apr 11 2026)
- Paper ID
- 7517
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 4.1905499e-05
- Overall Rank
- 10,204 | 29.09%
- DOI
-
10.1145/3786690
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 210 |
Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph |
2019 |
VLDB |
0.00034086264 |
| 596 |
Query-Aware Locality-Sensitive Hashing for Approximate Nearest Neighbor Search |
2016 |
VLDB |
0.00019455943 |
| 730 |
AnalyticDB-V: A Hybrid Analytical Engine Towards Query Fusion for Structured and Unstructured Data |
2020 |
VLDB |
0.00017443615 |
| 763 |
A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search |
2021 |
VLDB |
0.00016963981 |
| 1,225 |
SK-LSH : An Efficient Index Structure for Approximate Nearest Neighbor Search |
2014 |
VLDB |
0.00013182109 |
| 2,002 |
Efficient Approximate Nearest Neighbor Search in Multi-dimensional Databases |
2023 |
SIGMOD |
9.8258191e-05 |
| 2,287 |
RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search |
2024 |
SIGMOD |
9.1004806e-05 |
| 2,687 |
HVS: Hierarchical Graph Structure Based on Voronoi Diagrams for Solving Approximate Nearest Neighbor Search |
2022 |
VLDB |
8.3079951e-05 |
| 3,541 |
Similarity search in the blink of an eye with compressed indices |
2023 |
VLDB |
6.9910982e-05 |
| 4,600 |
Practical and Asymptotically Optimal Quantization of High-Dimensional Vectors in Euclidean Space for Approximate Nearest Neighbor Search |
2025 |
SIGMOD |
6.0528015e-05 |
| 4,622 |
Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Art |
2025 |
SIGMOD |
6.0356382e-05 |
| 5,236 |
RoarGraph: A Projected Bipartite Graph for Efficient Cross-Modal Approximate Nearest Neighbor Search |
2024 |
VLDB |
5.6077913e-05 |
| 5,690 |
FARGO: Fast Maximum Inner Product Search via Global Multi-Probing |
2023 |
VLDB |
5.3699421e-05 |
| 6,375 |
DET-LSH: A Locality-Sensitive Hashing Scheme with Dynamic Encoding Tree for Approximate Nearest Neighbor Search |
2024 |
VLDB |
5.0868008e-05 |
| 8,484 |
Maximum Inner Product is Query-Scaled Nearest Neighbor |
2025 |
VLDB |
4.4956257e-05 |
| 9,399 |
BigVectorBench: Heterogeneous Data Embedding and Compound Queries are Essential in Evaluating Vector Databases |
2025 |
VLDB |
4.3399748e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 10,154 |
Distribution-Aware Exploration for Adaptive HNSW Search |
2026 |
SIGMOD |
4.1905499e-05 |
| 7,856 |
Adaptable Similarity Search using Non-Relevant Information |
2002 |
VLDB |
4.6304319e-05 |
| 10,284 |
An Experimental Evaluation of Hybrid Querying on Vectors |
2026 |
VLDB |
4.1905499e-05 |
| 9,399 |
BigVectorBench: Heterogeneous Data Embedding and Compound Queries are Essential in Evaluating Vector Databases |
2025 |
VLDB |
4.3399748e-05 |
| 10,160 |
Efficient Vector Index Merging in Vector Databases |
2026 |
SIGMOD |
4.1905499e-05 |
| 2,321 |
High-Throughput Vector Similarity Search in Knowledge Graphs |
2023 |
SIGMOD |
9.0359336e-05 |
| 4,622 |
Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Art |
2025 |
SIGMOD |
6.0356382e-05 |
| 4,193 |
New Trends in High-D Vector Similarity Search: AI-driven, Progressive, and Distributed |
2021 |
VLDB |
6.3657766e-05 |
| 10,158 |
Efficient and Robust Out-Of-Distribution Vector Similarity Search with Cross-Distribution Monotonic Graph |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,090 |
Integrating Vector Databases across Embedding Models |
2026 |
SIGMOD |
4.1905499e-05 |