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Diagnosing LLM Reranker Behavior Under Fixed Evidence Pools

Arat, Baris et al.
arXiv (All) · Papers
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computation-and-languageinformation-retrievalmachine-learning
Standard reranking evaluations study how a reranker orders candidates returned by an upstream retriever. This setup couples ranking behavior with retrieval quality, so differences in output cannot be attributed to the ranking policy alone. We introduce a controlled diagnostic for reranking that uses
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