Papers with query optimizer

1 papers
Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models (2025.findings-emnlp)

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Challenge: Extract-Refine-Retrieve-Read is a query optimization framework for large language models . it is designed to bridge the pre-retrieval information gap in Retriev-Augmented Generation systems .
Approach: They propose a framework to extract parametric knowledge from Large Language Models and refine them using a specialized query optimizer.
Outcome: The extract-refine-retrieve-read framework outperforms baselines on QA datasets . it is designed to meet the knowledge requirements of large language models (LLMs)

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