GRAB-ANNS is a new GPU graph index that achieves up to 240x higher hybrid search throughput via bucket layouts and hybrid intra/inter-bucket edges.
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4 Pith papers cite this work. Polarity classification is still indexing.
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Veda and EffVeda partition vector data by role combinations, apply lattice-based copy/merge under storage budget, index large nodes with HNSW and small nodes with linear scan, then use query plans and coordinated search with pruning to answer authorized top-k queries.
DocMaster builds hierarchical document trees and multi-view semantic indices (PC-KMeans clusters plus hyper-edges) for structure-aware filtering and RAG over complex document collections.
citing papers explorer
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GRAB-ANNS: High-Throughput Indexing and Hybrid Search via GPU-Native Bucketing
GRAB-ANNS is a new GPU graph index that achieves up to 240x higher hybrid search throughput via bucket layouts and hybrid intra/inter-bucket edges.
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Don't Stir the Pot! Authorized Vector Data Retrieval via Access-Aware Indexing
Veda and EffVeda partition vector data by role combinations, apply lattice-based copy/merge under storage budget, index large nodes with HNSW and small nodes with linear scan, then use query plans and coordinated search with pruning to answer authorized top-k queries.
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DocMaster: A Hierarchical Structure-Aware System for Document Analysis
DocMaster builds hierarchical document trees and multi-view semantic indices (PC-KMeans clusters plus hyper-edges) for structure-aware filtering and RAG over complex document collections.
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