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arXiv · 2602.23184

MTRAG-UN: A Benchmark for Open Challenges in Multi-Turn RAG Conversations

Sara Rosenthal·Yannis Katsis·Vraj Shah·Lihong He·Lucian Popa·Marina Danilevsky
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Abstract

We present MTRAG-UN, a benchmark for exploring open challenges in multi-turn retrieval augmented generation, a popular use of large language models. We release a benchmark of 666 tasks containing over 2,800 conversation turns across 6 domains with accompanying corpora. Our experiments show that retrieval and generation models continue to struggle on conversations with UNanswerable, UNderspecified, and NONstandalone questions and UNclear responses. Our benchmark is available at https://github.com/IBM/mt-rag-benchmark

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Sara Rosenthal, Yannis Katsis, Vraj Shah, Lihong He, Lucian Popa, Marina Danilevsky. 2026-02-26. MTRAG-UN: A Benchmark for Open Challenges in Multi-Turn RAG Conversations. https://arxiv.org/abs/2602.23184

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