Abstract: Approximate K Nearest Neighbor (AKNN) search in high-dimensional spaces is a critical yet challenging problem. In AKNN search, distance computation is the core task that dominates the ...

An analysis of star movements from the Gaia spacecraft reveals that the Small Magellanic Cloud — a satellite galaxy bound to the Milky Way — is being torn apart by its larger neighbor. When you ...

A sophisticated cyber-espionage attack used by notorious Russian advanced persistent threat (APT) Fancy Bear at the outset of the current Russia-Ukraine war demonstrates a novel attack vector that a ...

Graph-based methods have become increasingly important in data retrieval and machine learning, particularly in nearest neighbor (NN) search. NN search helps identify data points closest to a given ...

The k-nearest neighbors (KNN) regression method, known for its nonparametric nature, is highly valued for its simplicity and its effectiveness in handling complex structured data, particularly in big ...

Large language models (LLMs) have proven their potential to handle multiple tasks and perform extremely well across various applications. However, it is challenging for LLMs to generate accurate ...

A technical paper titled “Bridging Software-Hardware for CXL Memory Disaggregation in Billion-Scale Nearest Neighbor Search” was published by researchers at the Korea Advanced Institute of Science and ...

PyTorch + HuggingFace code for RetoMaton: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022), including an implementation of kNN-LM and kNN-MT ...