Cost-Efficient RAG for Entity Matching with LLMs: A Blocking-based Batch Processing Framework

Name: Cost-Efficient RAG for Entity Matching with LLMs: A Blocking-based Batch Processing Framework
Uploaded: 2026-10-17T08:16:46.092933+00:00
Duration: 426 s
Description: The CE-RAG4EM framework improves entity matching quality while significantly reducing computational cost by using blocking-based batch retrieval and generation. It addresses the expense of large-scale Retrieval-Augmented Generation (RAG) for entity matching by grouping similar records, leading to comparable or better F1 scores on challenging datasets with sparse attributes.

The CE-RAG4EM framework improves entity matching quality while significantly reducing computational cost by using blocking-based batch retrieval and generation. It addresses the expense of large-scale Retrieval-Augmented Generation (RAG) for entity matching by grouping similar records, leading to comparable or better F1 scores on challenging datasets with sparse attributes.

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