arXiv:2607. 01283v1 Announce Type: cross Abstract: Grid-based approaches to approximate nearest neighbor (ANN) search have been absent from modern scaling analyses.
arXiv:2607. 17582v1 Announce Type: new Abstract: Approximate Nearest Neighbor Search (ANNS) plays a pivotal role in modern deep learning pipelines.
arXiv:2603. 06660v2 Announce Type: replace-cross Abstract: Approximate Nearest Neighbor Search (ANNS) is fundamental to modern AI applications.
arXiv:2609. 02143v1 Announce Type: cross Abstract: Most vector databases rely on graph-based indexes, notably HNSW and Vamana, for approximate nearest neighbor search.
Approximate Nearest Neighbor Search (ANNS) plays a pivotal role in modern deep learning pipelines. Recently, many ANNS systems have been proposed to either provide broad functionality or reach high performance.
arXiv:2411. 03253v2 Announce Type: replace-cross Abstract: We propose a general framework for end-to-end learning of data structures.
arXiv:2608. 16270v1 Announce Type: new Abstract: Coreset selection reduces the cost of model training by replacing a large training set with a small representative subset.
arXiv:2608. 15438v1 Announce Type: cross Abstract: Building approximate nearest neighbor (ANN) indexes at billion scale is often dominated by expensive global clustering or graph construction, making time-to-index a first-order systems concern.
arXiv:2510.23039v2 Announce Type: replace Abstract: Approximate Nearest Neighbor (ANN) search and Approximate Kernel Density Estimation (A-KDE) are fundamental problems at the core of modern machine...
arXiv:2503. 01805v3 Announce Type: replace-cross Abstract: Transformers have revolutionized the field of machine learning.
arXiv:2601. 07048v5 Announce Type: replace-cross Abstract: Approximate nearest neighbor search (ANNS) is a core problem in machine learning and information retrieval applications.
arXiv:2606. 04522v1 Announce Type: cross Abstract: Approximate nearest neighbor (ANN) search has become a core primitive in information retrieval and modern machine learning tasks, from classification to retrieval-augmented generation.
arXiv:2510. 00566v4 Announce Type: replace-cross Abstract: Approximate Nearest-Neighbor Search (ANNS) pipelines for high-dimensional neural embeddings spend the bulk of their query time in candidate verification, making it the primary bottleneck in the search process.