Papers by Marco Wrzalik

1 papers
CoRT: Complementary Rankings from Transformers (2021.naacl-main)

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Challenge: Recent approaches to information retrieval mitigate computational costs by using a multi-stage ranking pipeline.
Approach: They propose a ranking model that leverages contextual representations from pre-trained language models to complement term-based ranking functions while causing no significant delay at query time.
Outcome: The proposed model significantly increases candidate recall by complementing BM25 with missing candidates while causing no significant delay at query time.

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