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Per-Query Gating of LLM Rerankers for Multi-Hop Retrieval

Bacellar, Andre
arXiv (All) · Papers
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computation-and-languageinformation-retrievalmachine-learning
LLM rerankers add of the order of \$0.2-0.3 per 1,000 queries and about a second of tail latency on top of a graph-augmented dense pipeline such as HippoRAG2, and on three multi-hop benchmarks they improve final-hop top-K coverage on seven of nine (dataset, K) cells, by up to +34.8 pp. We ask whethe
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