AI Often Cites Web Pages It Has Never Even Read
Unite.AI, Friday, October 16th, 2026
Imperial College research finds search-augmented LLMs often answer from snippets without opening sources, producing stale answers and bad citations.
The article covers the Imperial College London paper "Retrieved but Not Read," which tested GPT-5.6 Luna and six open-weight configurations on hundreds of facts that changed after training cutoffs.
Models frequently answered without opening any retrieved pages, sometimes in more than half of searches, and this was associated with higher rates of outdated answers and citations that contradicted their claims.
Supplying correct evidence directly reduced failures, though some models still favored outdated knowledge.
The findings matter for anyone relying on RAG or AI search citations.