arXiv:2610.07266v1 Announce Type: new Abstract: Retriever upgrades are typically evaluated using aggregate metrics, which can hide regressions on queries the previous retriever already served correctly. We study these regressions as negative flips: queries for which BM25 retrieves a judged relevant passage and the replacement does not. We evaluate BGE-large, E5-large-v2, and SPLADE on three BEIR collections: Natural Questions, HotpotQA, and FiQA, across five retrieval depths. All replacements improve overall retrieval coverage. Negative flips occur in every setting and vary substantially by corpus, retriever, and depth. At k=1, 8.6-37.5% of BM25 successes are lost across the evaluated settings. Negative-flip rates are lower in the larger-depth settings, where the BM25-supported cohort is defined separately at each depth. These rates use the any-relevant support label. On HotpotQA at k=10, requiring every positive qrel passage raises the negative-flip rate to 12.3-17.3%. Simple fixed-budget combinations with BM25 reduce these regressions, and a HotpotQA reader experiment provides a limited downstream check in which some retrieval flips are accompanied by answer regressions. These results motivate evaluating retriever updates using query-level compatibility alongside aggregate retrieval quality.