More Context, Same Budget: Dual-Bounded Relational Recall Beyond Top-K Retrieval
More context does not require a larger retrieval budget. Under the same ceiling, a retrieval system can recover more of the evidence a question requires by following relationships between evidence that flat top-k ranking leaves behind. We test that proposition with Dual-Bounded Relational Recall (DBRR), which allocates a fixed retrieval budget between relevance-selected seeds and bounded graph-adjacent context, against matched flat top-k retrieval using the same relevance-ranking stage and the same maximum number of retrieval units and tokens. The outcome is complete recovery of the official HotpotQA supporting-evidence set for each question. Across 7,405 FullWiki questions, the Primary D...
| Authors | Thomson D. Nguy |
|---|---|
| Primary category | cs.IR |
| Published | 19 August 2026 |
| Last updated at source | 19 August 2026 |
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