A New Role for Relevance: Guiding Corpus Interaction in Agentic Search
Relevance is a query-dependent estimate of whether a document or excerpt contains useful evidence. Existing retrieval agents use relevance to select top-$k$ content, but document relevance alone cannot localize, compose, or verify the evidence required by complex questions. Direct Corpus Interaction (DCI) enables such fine-grained operations through grep-style exploration, but its relevance-agnostic search can expose useful clues late and delay convergence. Recent advances use relevance to narrow the corpus into a working space for interaction. Once interaction begins, however, relevance still does not directly guide which documents grep searches first or distinguish informative excerpts ...
| Authors | Jiangnan Li, Yuqing Li, Mo Yu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 27 July 2026 |
| Last updated at source | 3 August 2026 |
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