Glossary · Retrieval & generation
Recall@K
For one query, Recall@K is `|relevant items intersecting the top k| / |relevant items|`. A dataset score aggregates those per-query values under a stated rule.
Why it matters
It tells you whether a retrieval stage supplies downstream generation or reranking with enough relevant candidates.
In practice
Define relevance judgments, k, the aggregation method, and a policy for queries with no judged relevant items, then inspect queries with zero recalled evidence.
Common confusion
High Recall@K does not mean the top result is good, the ranking is well ordered, or the final answer is grounded. Queries with no relevant items require an explicit exclusion or assigned-value policy because the denominator is zero.
Related terms
Sources
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