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pro vyhledávání: '"Jaenich, Thomas"'
This paper describes our participation in the TREC 2023 Deep Learning Track. We submitted runs that apply generative relevance feedback from a large language model in both a zero-shot and pseudo-relevance feedback setting over two sparse retrieval ap
Externí odkaz:
http://arxiv.org/abs/2405.01122
Multilingual information retrieval (MLIR) considers the problem of ranking documents in several languages for a query expressed in a language that may differ from any of those languages. Recent work has observed that approaches such as combining rank
Externí odkaz:
http://arxiv.org/abs/2405.00978
The main objective of an Information Retrieval system is to provide a user with the most relevant documents to the user's query. To do this, modern IR systems typically deploy a re-ranking pipeline in which a set of documents is retrieved by a lightw
Externí odkaz:
http://arxiv.org/abs/2401.13434