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arXiv · 2506.06015

On the Merits of LLM-Based Corpus Enrichment

Gal Zur·Tommy Mordo·Moshe Tennenholtz·Oren Kurland
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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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Gal Zur, Tommy Mordo, Moshe Tennenholtz, Oren Kurland. 2025-06-06. On the Merits of LLM-Based Corpus Enrichment. https://arxiv.org/abs/2506.06015

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