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A collection of AWESOME things about Graph-Related LLMs.
[SIGMOD 2023] High-Dimensional Approximate Nearest Neighbor Search: with Reliable and Efficient Distance Comparison Operations
Residual Quantization with Implicit Neural Codebooks
This is a repository of public data sources for Recommender Systems (RS).
A curated list of awesome works related to high dimensional structure/vector search & database
Approximate Nearest Neighbor search using reduced-rank regression, with extremely fast queries, tiny memory usage, and rapid indexing on modern vector embeddings.
Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data
A new query hardness measure for graph-based ANN indexes. Build unbiased workloads with this hardness to see the actual performance of your ANN indexes.
fast library for ANN search and KNN graph construction
A library of algorithms for approximate nearest neighbor search in high dimensions, along with a set of useful tools for designing such algorithms.
Everything you always wanted to know about ANNS but were afraid to ask 🥰
📚 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-sca…
This is the implementation of the Hierarquical Clustering-based Nearest Neighbor Graphs
Header-only C++/python library for fast approximate nearest neighbors
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
Code repository for the paper - "AdANNS: A Framework for Adaptive Semantic Search"
[SIGMOD 2024] RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search
Graph-structured Indices for Scalable, Fast, Fresh and Filtered Approximate Nearest Neighbor Search