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How Calibration Content Shapes Attention-Based Reranking

Karypis, Petros et al.
arXiv (All) · Papers
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computation-and-languageinformation-retrieval
Attention-based rerankers score documents by aggregating query-to-document attention and subtracting a null-query calibration pass to remove positional and structural bias. Although widely used, this calibration assumes that the null pass removes irrelevant signal from each document. We show that mo
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