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Pierre Erbacher

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Jul 2026

RAGnRoll: Learning to Iteratively Retrieve and Generate Attributable Answer Snippets

This work proposes RAGnRoll, a language model for attributed answer generation within a multi-round Retrieval-Augmented Generation (RAG) framework that leverages the iterative nature of multi-round RAG to train an LLM to incrementally build answers guided by subqueries.

Hanane Djeddal, Laure Soulier, K. Pinel-Sauvagnat et al. · 0 citations