A blocking-plus-LLM-matching method delivers higher precision and broader coverage than threshold or top-K baselines while maintaining comparable recall on ICD version mapping tasks.
Kcmf: A knowledge-compliant framework for schema and entity matching with fine-tuning-free llms
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
RedParrot accelerates NL-to-DSL conversion by 3.6x with 8.26% accuracy gain on enterprise data and 34.8% on benchmarks via semantic caching of query skeletons and contrastive learning.
ConStruM improves LLM-based schema matching by using a context tree and global similarity hypergraph to assemble query-specific evidence packs from available schema metadata.
citing papers explorer
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Managing Map Cardinality in Automatic Disease Classification Mapping: Balancing Precision, Recall and Coverage
A blocking-plus-LLM-matching method delivers higher precision and broader coverage than threshold or top-K baselines while maintaining comparable recall on ICD version mapping tasks.
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RedParrot: Accelerating NL-to-DSL for Business Analytics via Query Semantic Caching
RedParrot accelerates NL-to-DSL conversion by 3.6x with 8.26% accuracy gain on enterprise data and 34.8% on benchmarks via semantic caching of query skeletons and contrastive learning.
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ConStruM: A Structure-Guided LLM Framework for Context-Aware Schema Matching
ConStruM improves LLM-based schema matching by using a context tree and global similarity hypergraph to assemble query-specific evidence packs from available schema metadata.