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AHIR: Deep learning-based autoencoder hashing image retrieval

Scaling Laws for Grid-Based Approximate Nearest Neighbor Search in High Dimensions

Grid-based approaches to approximate nearest neighbor (ANN) search have been absent from modern scaling analyses. We present a systematic characterization of a multiprobe

Deep Distance Weighted Sampling Hashing for Cross-modal Retrieval

HotSpotter - Patterned Species Instance Recognition

We present HotSpotter, a fast, accurate algorithm for identifying individual animals against a labeled database. It is not species specific and has been applied to Grevy's and plai…

Deep Stochastic Spherical Hashing With Von Mises-Fisher Distributions for Cross-Modal Retrieval

Deep cross-modal hashing is widely studied for its low storage cost and high retrieval efficiency. Despite recent progress, existing deep cross-modal hashing methods still face cri…

Exploring Human Perception-Aligned Perceptual Hashing

The widespread sharing of images has led to challenges in controlling the spread of harmful content in consumer devices, particularly child sexual abuse material. Perceptual hashin…

HNSW with Accuracy Guarantees Using Graph Spanners -- A Technical Report

Hierarchical Navigable Small World (HNSW) graphs serve as the industry standard due to their logarithmic complexity and strong empirical performance. However, HNSW relie

GORIO: GPU-Centered Remote I/O for Graph ANNS over NVMe-oF

Graph-based approximate nearest neighbor search (ANNS) is increasingly used in vector databases and retrieval-augmented generation services, but large vector ind

Online K-d tree for approximate neighborhood search in data streams

The k-Nearest Neighbors (kNN) algorithm has long been widely used in Machine Learning (ML) applications. However, the main concern when using it is the computational cost required …

Parallel Metric Skiplists and Nearest Neighbor Search

The metric skip-list is a data structure designed for efficient nearest and $k$-nearest neighbor search in metric spaces. For many real-world datasets with reasonable dist

ACRONYM: Accelerated Approximate Nearest Neighbor Search in Memory for Dynamic Vector Databases

Vector database search with frequent updates is increasingly critical in applications such as retrieval augmented generation, recommendation systems, and large-scale embedding retr…

HRNN: A Hybrid Graph Index for Approximate Reverse k-Nearest Neighbor Search on High-Dimensional Vectors

Reverse k-nearest neighbor (RkNN) search returns all data points that regard a query vector as one of their k-nearest neighbors (kNNs). Existing RkNN methods typically follow a fil…

Fast Exact Nearest-Neighbor Learning for High-Frequency Financial Time Series

AI efficiency at scale is becoming critical in finance as market data volumes surge across equities, ETFs, FX, options, and high-frequency trading streams. This growth creates a co…

Efficient Graph Indexing for Interval-Aware Vector Search

Interval-aware Approximate Nearest Neighbor (ANN) search arises in applications where each object is associated with a numeric value or interval, and queries must satisfy both vect…

Unified Dominance Graph for Interval-Predicate Approximate Nearest Neighbor Search

Approximate Nearest Neighbor Search (ANNS) is a core primitive for unstructured data retrieval. Real-world applications--such as temporal databases, financial data analy

Deep Softtriple hashing for Multi-Label cross-modal retrieval

Hashing techniques are widely adopted in large-scale retrieval due to their low time and space complexity. Existing deep cross-modal hashing methods mostly rely on mini-batch train…

Deep synthetic-proxy hashing for multi-label cross-modal retrieval

Deep noise-tolerant hashing for remote sensing image retrieval

RFHNet: Relational and Frequency-Aware Hashing Network for Large-Scale Fine-Grained Food Image Retrieval

Fine-grained food image retrieval is a key task in computational gastronomy, with applications in food traceability, dietary monitoring, and smart catering systems. Althou

CS-PQ: Cache-Friendly SIMD Product Quantization for Large-Scale ANNS Index Construction

Product Quantization (PQ) construction is deeply integrated into vector index construction for Approximate Nearest Neighbor Search (ANNS). The rapid growth in vector dimensionality…

Generalized Range Filtering Approximate Nearest Neighbor Search: Containment and Overlap [Technical Report]

Approximate nearest neighbor (ANN) search with range filters has recently garnered significant attention. This paper delves into a generalized form of this problem, i.e., ANN searc…

RT-RkNN: Reverse k Nearest Neighbor Queries as a Graphics Ray Casting Problem

Reverse k nearest neighbor (RkNN) queries are fundamental in spatial databases, location-based analytics, and recommendation systems. Existing state-of-the-art techniques

Slipstream: Locality-Aware Graph Index Construction for Streaming Approximate Nearest Neighbor Search

Graph indexes are widely used for high-recall approximate nearest neighbor search (ANNS), but many real-time applications require streaming ANNS. In these real-time applications, c…

SIEVE: Effective Filtered Vector Search with Collection of Indexes

Many real-world tasks such as recommending videos with the kids tag can be reduced to finding most similar vectors associated with hard predicates. This task, filtered vector searc…