On the Merits of LLM-Based Corpus Enrichment

• URL: http://arxiv.org/abs/2506.06015v1
• Date: Fri, 06 Jun 2025 12:02:14 GMT
• Title: On the Merits of LLM-Based Corpus Enrichment
• Authors: Gal Zur, Tommy Mordo, Moshe Tennenholtz, Oren Kurland,
• Abstract summary: We argue for a novel perspective: using genAI to enrich a document corpus.<n>The enrichment is based on modifying existing documents or generating new ones.
• Score: 11.398498369228571
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Generative AI (genAI) technologies -- specifically, large language models (LLMs) -- and search have evolving relations. We argue for a novel perspective: using genAI to enrich a document corpus so as to improve query-based retrieval effectiveness. The enrichment is based on modifying existing documents or generating new ones. As an empirical proof of concept, we use LLMs to generate documents relevant to a topic which are more retrievable than existing ones. In addition, we demonstrate the potential merits of using corpus enrichment for retrieval augmented generation (RAG) and answer attribution in question answering.

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