Semantic search retrieves substantially more implicit receptions of Locke's work than lexical baselines in 18th-century corpora, yet remains constrained by lexical gatekeeping.
Mazaré, P.E., Lomeli, M., Hosseini, L., Jégou, H.: The faiss library
5 Pith papers cite this work, alongside 309 external citations. Polarity classification is still indexing.
5
Pith papers citing it
309
external citations · external index
citation-role summary
baseline 1
citation-polarity summary
years
2026 5roles
baseline 1polarities
baseline 1representative citing papers
A perspective-conditioned RAG architecture is proposed for AI-assisted LCA interpretation, using scenario anchors, micro-queries, and neutral synthesis, demonstrated on a hydrogen diesel reduction case in Italian apple production.
SOLANET is a distributed GPU toolkit for neighbor graph construction that reports 11X speedup on 512 APUs for 1B points and 6.9X for 2B points.
Skills-aware RAG and multi-task learning approaches using a 33-skill dictionary significantly outperform baselines in classifying teachers' Van Hiele levels from 226 open-ended geometry responses.
Relational engines achieve faster SQL+vector-search queries on GPU than CPU when using compact vector indexes and fast interconnects, reversing the CPU-only design in current systems.
citing papers explorer
-
Matching Meaning at Scale: Evaluating Semantic Search for 18th-Century Intellectual History through the Case of Locke
Semantic search retrieves substantially more implicit receptions of Locke's work than lexical baselines in 18th-century corpora, yet remains constrained by lexical gatekeeping.
-
LCAi: Life Cycle Assessment with big data fusion and retrieval-augmented generation-assisted interpretation
A perspective-conditioned RAG architecture is proposed for AI-assisted LCA interpretation, using scenario anchors, micro-queries, and neutral synthesis, demonstrated on a hydrogen diesel reduction case in Italian apple production.
-
SOLANET: Distributed Neighbor Graph Construction on GPU-Accelerated Systems
SOLANET is a distributed GPU toolkit for neighbor graph construction that reports 11X speedup on 512 APUs for 1B points and 6.9X for 2B points.
-
Automatically Inferring Teachers' Geometric Content Knowledge: A Skills Based Approach
Skills-aware RAG and multi-task learning approaches using a 33-skill dictionary significantly outperform baselines in classifying teachers' Van Hiele levels from 226 open-ended geometry responses.
-
To GPU or Not to GPU: Vector Search in Relational Engines
Relational engines achieve faster SQL+vector-search queries on GPU than CPU when using compact vector indexes and fast interconnects, reversing the CPU-only design in current systems.