vector-search-papers
A curated GitHub repository of research papers and technical blogs focused on vector search, approximate nearest neighbor search (ANN Search), and vector databases. This resource serves as a comprehensive directory for foundational and cutting-edge research, making it highly relevant for anyone building or exploring vector database technologies.
About this tool
vector-search-papers
A curated GitHub repository collecting research papers and technical blogs on vector search, approximate nearest neighbor search (ANN Search), and vector databases. This resource is designed as a comprehensive directory for foundational and advanced research in vector search technologies, relevant for information retrieval, RAG (retrieval-augmented generation), recommendation systems, and more.
Features
- Curated Paper List: Extensive, regularly updated collection of research papers and technical articles on:
- Vector search fundamentals and applications
- Approximate nearest neighbor search (ANN/ANNS) methods
- Vector databases and indexing strategies
- Graph-based, GPU-based, MIPS, LSH, and other algorithmic categories
- Theoretical and survey works, as well as practical system designs
- Application Coverage: Papers cover vector search applications in areas such as:
- Large-scale information retrieval
- Cross-modal retrieval
- LLMs-based RAG
- Recommendation systems
- Drug discovery
- Image search
- LLM inference
- Introductory Resources: Links to beginner-friendly explanations and introductory articles about vector search and its importance
- Community Contributions: Open for public contributions to add new papers or resources
- Categorized Table: Papers organized in a table by title, category, and remarks for easy navigation
- Open Source: MIT license
Category
Curated Resource Lists
Tags
vector-search, research, papers, ann, vector-databases
Source
https://github.com/matchyc/vector-search-papers
Pricing
- Free (Open Source, MIT License)
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