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3 Pith papers cite this work. Polarity classification is still indexing.

3 Pith papers citing it

fields

cs.DB 3

years

2026 1 2025 2

representative citing papers

PLOP: Cost-Based Placement of Semantic Operators in Hybrid Query Plans

cs.DB · 2026-04-10 · conditional · novelty 7.0

PLOP is a cost-based optimizer that finds optimal placements for semantic LLM operators in hybrid query plans via dynamic programming, delivering up to 1.5x speedup and 4.29x cost reduction on 44 benchmark queries while preserving accuracy.

Cortex AISQL: A Production SQL Engine for Unstructured Data

cs.DB · 2025-11-10 · unverdicted · novelty 6.0

Snowflake's Cortex AISQL adds native semantic operations to SQL via AI-aware optimization, adaptive model cascades, and semantic join rewriting, delivering 2-70x speedups in production workloads.

ScaleDoc: Scaling LLM-based Predicates over Large Document Collections

cs.DB · 2025-09-16 · unverdicted · novelty 6.0

ScaleDoc achieves over 2x end-to-end speedup and up to 85% fewer LLM invocations for semantic predicates on large document collections via offline LLM representations, contrastive-trained proxy filtering, and adaptive cascades.

citing papers explorer

Showing 3 of 3 citing papers.

  • PLOP: Cost-Based Placement of Semantic Operators in Hybrid Query Plans cs.DB · 2026-04-10 · conditional · none · ref 14

    PLOP is a cost-based optimizer that finds optimal placements for semantic LLM operators in hybrid query plans via dynamic programming, delivering up to 1.5x speedup and 4.29x cost reduction on 44 benchmark queries while preserving accuracy.

  • Cortex AISQL: A Production SQL Engine for Unstructured Data cs.DB · 2025-11-10 · unverdicted · none · ref 16

    Snowflake's Cortex AISQL adds native semantic operations to SQL via AI-aware optimization, adaptive model cascades, and semantic join rewriting, delivering 2-70x speedups in production workloads.

  • ScaleDoc: Scaling LLM-based Predicates over Large Document Collections cs.DB · 2025-09-16 · unverdicted · none · ref 17

    ScaleDoc achieves over 2x end-to-end speedup and up to 85% fewer LLM invocations for semantic predicates on large document collections via offline LLM representations, contrastive-trained proxy filtering, and adaptive cascades.