Coverage, Not Averages: Semantic Stratification for Trustworthy Retrieval Evaluation
Retrieval quality is the primary bottleneck for accuracy and robustness in retrieval-augmented generation (RAG). Current evaluation relies on heuristically constructed query sets, which introduce a hidden intrinsic bias. We formalize retrieval evaluation as a statistical estimation problem, showing that metric reliability is fundamentally limited by the evaluation-set construction. We further introduce \emph{semantic stratification}, which grounds evaluation in corpus structure by organizing documents into an interpretable global space of entity-based clusters and systematically generating queries for missing strata. This yields (1) formal semantic coverage guarantees across retrieval reg...
| Authors | Andrew Klearman, Radu Revutchi, Rohin Garg et al. |
|---|---|
| Primary category | cs.IR |
| Published | 22 April 2026 |
| Last updated at source | 22 April 2026 |
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