ybtsdst / vector-search-papers

๐Ÿ“š Awesome papers and technical blogs on vector DB (database), semantic-based vector search or approximate nearest neighbor search (ANN Search, ANNS). Vector search is the key component of large-scale information retrieval, cross-modal retrieval, LLMs-based RAG, vector databases.

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Vector Search, Approximate Nearest Neighbor Search Papers

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A curated collection of awesome papers in the field of vector search, known as approximate nearest neighbor search (ANN search, ANNS). This repository aims to gather high-quality research papers, articles, and resources that provide valuable insights and advancements. This technology is a critical component in vector databases, retrieval-augmented generation (RAG), large-scale information retrieval, recommendation systems, drug discovery, image search, etc.

Table of Contents

What is vector search and its applications

First of all, what is vector search, and why is it so important in the booming age of AI?

simple explanation:

Applications:

Papers

Title Url High-Level Category Remarks
Approximate Nearest Neighbor Search on High Dimensional Data โ€” Experiments, Analyses, and Improvement Link Survey
Graph-based Nearest Neighbor Search: From Practice to Theory Link Theoretical
FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search Link Graph-based
HVS: hierarchical graph structure based on Voronoi diagrams for solving approximate nearest neighbor search Link Graph-based
DiskANN: Fast Accurate Billion-point Nearest Neighbor Search on a Single Node Link Graph-based SSD-based
Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs Link Graph-based
SONG: Approximate Nearest Neighbor Search on GPU Link Graph-based
Graph-based Nearest Neighbor Search: Promises and Failures Link Graph-based
Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination Link Graph-based
A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search Link Survey
Fast approximate nearest neighbor search with the navigating spreading-out graph Link Graph-based
Non-metric Similarity Graphs for Maximum Inner Product Search Link Graph-based
Understanding and Improving Proximity Graph-based Maximum Inner Product Search Link Graph-based
Learning to Route in Similarity Graphs Link Graph-based+DeepLearning(GCN)
Optimization of Indexing Based on k-Nearest Neighbor Graph for Proximity Search in High-dimensional Data Link Graph-based
Fast Approximate Nearest Neighbor Search with a Dynamic Exploration Graph using Continuous Refinement Link Graph-based
Efficient Approximate Nearest Neighbor Search in Multi-dimensional Databases Link Graph-based
Scaling Graph-Based ANNS Algorithms to Billion-Size Datasets: A Comparative Analysis Link Graph-based
SPANN: Highly-efficient Billion-scale Approximate Nearest Neighbor Search Link Graph-Tree-based SSD-based
Hierarchical Clustering-Based Graphs for Large Scale Approximate Nearest Neighbor Search Link Graph-based
Hierarchical Clustering-Based Graphs for Large Scale Approximate Nearest Neighbor Search Link Graph-based
Fusion of graph-based indexing and product quantization for ANN search Link Graph-based
Towards Efficient Index Construction and Approximate Nearest Neighbor Search in High-Dimensional Spaces Link Graph-based
Optimization of Indexing Based on k-Nearest Neighbor Graph for Proximity Search in High-dimensional Data Link Graph-based
Scaling Graph-Based ANNS Algorithms to Billion-Size Datasets: A Comparative Analysis Link Survey
Automating Nearest Neighbor Search Configuration with Constrained Optimization Link Learning
Approximate Nearest Neighbor Search under Neural Similarity Metric for Large-Scale Recommendation Link Graph-based
Norm Adjusted Proximity Graph for Fast Inner Product Retrieval Link Graph-based
On Efficient Retrieval of Top Similarity Vectors Link Graph-based
SONG: Approximate Nearest Neighbor Search on GPU Link GPU
RTNN: Accelerating Neighbor Search Using Hardware Ray Tracing Link GPU
Billion-scale similarity search with GPUs Link GPU
Fast neural ranking on bipartite graph indices Link Neural Rank
Fast Item Ranking under Neural Network based Measures Link Neural Rank
Non-metric Similarity Graphs for Maximum Inner Product Search Link MIPS
Mรถbius Transformation for Fast Inner Product Search on Graph Link MIPS
Understanding and Improving Proximity Graph-based Maximum Inner Product Search Link MIPS
Reinforcement Routing on Proximity Graph for Efficient Recommendation Link Learning
From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective Link Learning
Constructing Tree-based Index for Efficient and Effective Dense Retrieval Link Learning
Reverse Maximum Inner Product Search: Formulation, Algorithms, and Analysis Link MIPS
FARGO: Fast Maximum Inner Product Search via Global Multi-Probing Link LSH
SRS: solving c -approximate nearest neighbor queries in high dimensional Euclidean space with a tiny index Link LSH
From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective Link LSH
LazyLSH: Approximate Nearest Neighbor Search for Multiple Distance Functions with a Single Index Link LSH
HD-index: pushing the scalability-accuracy boundary for approximate kNN search in high-dimensional spaces Link LSH
Falconn++: A Locality-sensitive Filtering Approach for Approximate Nearest Neighbor Search Link LSH
Deep Semantic-Preserving Ordinal Hashing for Cross-Modal Similarity Search Link LSH
Supervised Hierarchical Deep Hashing for Cross-Modal Retrieval Link LSH
A Revisit of Hashing Algorithms for Approximate Nearest Neighbor Search Link Survey
Transformer Memory as a Differentiable Search Index Link Model-as-Index
Recommender Systems with Generative Retrieval Link Model-as-Index
SPREADING VECTORS FOR SIMILARITY SEARCH Link Learning + Dimensionality Reduction
Model-enhanced Vector Index Link Fusion Retrieval
GraSP: Optimizing Graph-based Nearest Neighbor Search with Subgraph Sampling and Pruning Link Prune edges with learning

Please note that some entries may require access or membership to view the full content.

How to Contribute

We welcome contributions to expand and improve this collection. If you have any papers or resources that you believe should be included, please follow these guidelines:

  1. Fork the repository.
  2. Add your paper/resource to the appropriate category or create a new category if needed.
  3. Include a link to the paper/resource (if available) or any relevant information.
  4. Submit a pull request.

License

MIT license.

About

๐Ÿ“š Awesome papers and technical blogs on vector DB (database), semantic-based vector search or approximate nearest neighbor search (ANN Search, ANNS). Vector search is the key component of large-scale information retrieval, cross-modal retrieval, LLMs-based RAG, vector databases.

License:MIT License