When Does Retrieval Hurt? Characterizing Negative Retrieval in RAG

Retrieval can supply knowledge that a language model lacks, but it can also overturn answers that the model already gives reliably without context. We study the second effect, answer preservation under retrieval, using an evaluation protocol that separates closed-book screening from fresh, paired closed-book and retrieval evaluation. On questions screened as reliably answered, the difference between retrieval error and fresh closed-book error measures net preservation loss; marginal error rates also give sharp bounds on harmful and beneficial answer changes. The protocol reports overall utility and preservation on explicitly defined question populations. On 3,250 questions from five QA benchmarks, top-10 retrieval raises the primary reader's overall accuracy by 9.5 points, yet raises its error on the 1,878 screened questions by 12.8 points relative to the fresh control. A matched intervention on 600 screened questions keeps complete supporting evidence and replaces a single distractor: in-context RAG makes 25, 47 and 111 errors with an unrelated, topical near-miss and conflicting distractor, respectively, whereas Astute RAG makes 14, 19 and 34. Supporting evidence therefore does not prevent content-dependent errors; the conflict-induced increase is 14.3 percentage points for in-context RAG and 3.3 for Astute RAG. Elementary probability identities connect these measurements and bound the paired harm that marginal error rates can identify.