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Affiliation:, University of Waterloo
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QueryRoute is introduced, a benchmark that freezes the expensive artifacts needed to study this inference-time decision problem reproducibly: original queries, generated variants, ranked lists under multiple retrievers, retrieval scores, and per-query oracle labels.
EviQE is proposed, which aggregates documents retrieved by multiple reformulators, selects a compact evidence set, and uses it for one grounded expansion step, which separates evidence selection from generation and treats reformulators as complementary retrieval perspectives.
LLM-powered query reformulation, a hot topic in IR, often fails to translate gains from lexical to neural retrieval, and bigger models don't always help.
Stop prompting LLMs to blindly rewrite queries – ReFormeR distills query transformations into reusable patterns that actually improve retrieval.
