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Equation 10 · From BM25 to Agentic Retrieval: A History of Retrieval-Augmented Generation

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qiq_i

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qiq_i

Symbol q_i

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subscript

subscript

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where f(qiq_i, D) is the frequency of query term qiq_i in D , |D| is the document’s length, avgdl\mathrm{avgdl} is the average document length in the collection, and k1k_1 and b are tuned constants controlling term-frequency saturation and length normalization respectively. The saturation term is the substantive advance over a raw term-frequency-times-IDF score: a term’s contribution grows quickly at first and then flattens, so a document that happens to repeat a query word fifty times does not dominate one that uses it three times in the right place. Decades later, this same function remains the default first-stage ranking method built into widely used open-source search engines, which is a strong…
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where f(qiq_i, D) is the frequency of query term qiq_i in D , |D| is the document’s length, avgdl\mathrm{avgdl} is the average document length in the collection, and k1k_1 and b are tuned constants controlling term-frequency saturation and length normalization respectively. The saturation term is the substantive advance over a raw term-frequency-times-IDF score: a term’s contribution grows quickly at first and then flattens, so a document that happens to repeat a query word fifty times does not dominate one that uses it three times in the right place. Decades later, this same function remains the default first-stage ranking method built into widely used open-source search engines, which is a strong claim to make about any piece of 1990s software and is offered here as an observation about longevity rather than as evidence that nothing since has improved on it.

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