Fast and Efficient Approximate Nearest Neighbor Search for High-Dimensional LLM Embeddings

2026-07-23

AI Summary

This work addresses the challenge of efficient approximate nearest neighbor search and maximum inner product search (MIPS) in high-dimensional embeddings from large language models. The authors propose a novel approach that transforms asymmetric MIPS into Euclidean nearest neighbor search via dimension augmentation, combined with Equi-Voronoi Polytopes (EVP) quantization and a Fast Linear Assignment Sorting (FLAS) one-dimensional pre-sorting mechanism. This integration substantially accelerates k-nearest neighbor graph (kNNG) construction and query processing while enhancing memory access locality and cache efficiency. Evaluated in the SISAP 2026 challenge, the method achieves low-latency, high-recall MIPS performance, significantly outperforming existing baselines.

Abstract

The annual SISAP Indexing Challenge benchmarks Approximate Nearest Neighbor Search (ANNS) algorithms under rigorous constraints. This paper presents our submissions for the 2026 edition, addressing both $k$-Nearest Neighbor Graph (kNNG) construction on 1024-dimensional BGE-M3 embeddings (Task 1) and Maximum Inner Product Search (MIPS) on unnormalized Llama-3.2-8B features (Task 2). To optimize construction speed, we utilize Equi-Voronoi Polytopes (EVP) for efficient quantization, supplemented by targeted reranking strategies to maintain high recall. For MIPS, we transform the asymmetric inner product problem into a Euclidean search space via dimensionality augmentation. To reduce query latency and optimize memory access, we introduce a 1D presorting mechanism via Fast Linear Assignment Sorting (FLAS) prior to graph construction. This significantly improves spatial locality and cache hit rates during subsequent graph traversal. Source Code: https://github.com/Visual-Computing/sisap26-deglib

Problem

• Approximate Nearest Neighbor Search
• k-Nearest Neighbor Graph
• Maximum Inner Product Search
• High-Dimensional Embeddings
• Large Language Model

Innovation

• Equi-Voronoi Polytopes
• Maximum Inner Product Search
• Fast Linear Assignment Sorting
• Approximate Nearest Neighbor Search
• k-Nearest Neighbor Graph