Titlebook: Advances in Information Retrieval; 46th European Confer Nazli Goharian,Nicola Tonellotto,Iadh Ounis Conference proceedings 2024 The Editor(

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Melina Heinemann,Karina Ratiner,Eran Elinavtructure. Predicting judgments from such documents becomes a challenging task, more so on documents with no structural annotation. We explore the classification of these large legal documents and their lack of structural information with a deep-learning-based hierarchical framework which we call MES

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Adaptive Significance of Circannual Rhythms,on can, for example, facilitate academic search, decision making, and knowledge graph construction. An important type of information not covered by existing approaches is hyperparameters. In this paper, we formalize and tackle hyperparameter information extraction (HyperPIE) as an entity recognition

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Mechanisms of Circannual Organization,search efforts to improve entity search methods, the availability of large-scale resources and extensible frameworks has been limiting progress. In this work, we present LaQuE (Large-scale Queries for Entity search), a curated framework for entity search, which includes a reproducible and extensible

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https://doi.org/10.1007/978-3-031-56060-6information retrieval; retrieval models and architectures; classification; query processing and ranking

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