Query recall determines the retrieval performance of classical Arabic poetry: BM25 and dense encoders show markedly divergent behavior as query abstraction increases.
A recent study published on October 26, 2026, on arXiv (arXiv:2610.31821v1) shows that, in classical Arabic poetry retrieval tasks, the degree to which users retain fragments of poetic lines—such as whether they can recall half a line—plays a more critical role in determining retrieval performance than model capabilities. BM25 outperforms all dense encoders, including state-of-the-art models with 8B parameters, on “tip-of-the-tongue” queries, but falls significantly behind on abstract queries.
Why it matters：This study, through systematic benchmarking using a bilingual corpus, a three-index model, and a dual-evaluation protocol, for the first time quantitatively reveals the dominant influence of query abstraction on different retrieval paradigms (lexical vs. dense), and—after being validated by both human annotators and open-source weight models—the conclusions demonstrate methodological universality and empirical robustness.