ModelRefs / Multi-Document Question Answering — AI Glossary
Multi-Document Question Answering — AI Glossary
A task requiring a model to synthesize information from multiple documents to answer a question, testing cross-document reasoning. Also called multi-doc QA.
Overview
Multi-document QA (HotpotQA, 2WikiMultiHop, MuSiQue) requires identifying relevant passages across documents, resolving coreferences, and synthesizing multi-hop reasoning chains. LLMs with long context can use context stuffing; RAG pipelines retrieve relevant documents. Benchmark for testing retrieval quality and reasoning depth.
Reference details
| Topic | prompting |
|---|---|
| Also known as | multi-doc QA |
| Last reviewed | 2026-06-24 |
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Frequently asked questions
What is Multi-Document Question Answering?
A task requiring a model to synthesize information from multiple documents to answer a question, testing cross-document reasoning.
Is Multi-Document Question Answering the same as multi-doc QA?
Yes — multi-doc QA are common aliases for Multi-Document Question Answering.
What concepts are related to Multi-Document Question Answering?
Closely related concepts include needle in haystack, open domain qa, rag.